Publications


Authors: Type:

2017

  • [DOI] C. P. M. P. Koolschijn, M. W. A. Caan, J. Teeuw, S. D. Olabarriaga, and H. M. Geurts, “Age-related differences in autism: the case of white matter microstructure,” Human Brain Mapping, vol. 38, iss. 1, pp. 82-96, 2017.
    [Bibtex]
    @article{Koolschijn:2017,
    Author = {Koolschijn, P C{\'e}dric M. P. and Caan, Matthan W. A. and Teeuw, Jalmar and Olabarriaga, S{\'\i}lvia D. and Geurts, Hilde M.},
    Date-Added = {2017-02-16 11:16:40 +0000},
    Date-Modified = {2017-02-16 11:16:55 +0000},
    Doi = {10.1002/hbm.23345},
    Isbn = {1097-0193},
    Journal = {{Human Brain Mapping}},
    Journal1 = {Hum. Brain Mapp.},
    Keywords = {autism; adults; DTI; white matter; underconnectivity; interference control; intra-individual variability},
    Number = {1},
    Pages = {82--96},
    Title = {Age-related differences in autism: The case of white matter microstructure},
    Ty = {JOUR},
    Url = {http://dx.doi.org/10.1002/hbm.23345},
    Volume = {38},
    Year = {2017},
    Bdsk-Url-1 = {http://dx.doi.org/10.1002/hbm.23345}}
  • [DOI] K. Maheshwari, D. Katz, S. D. Olabarriaga, J. Wozniak, and D. Thain, “Report on the first workshop on negative and null results in eScience,” Concurrency and Computation: Practice and Experience, vol. 29, iss. 2, p. e3908–n/a, 2017.
    [Bibtex]
    @article{Maheshwari:2017,
    Author = {Maheshwari, Ketan and Katz, Daniel and Olabarriaga, Silvia D. and Wozniak, Justin and Thain, Douglas},
    C7 = {e3908},
    C8 = {cpe.3908},
    Date-Added = {2017-02-16 11:14:21 +0000},
    Date-Modified = {2017-02-16 11:14:51 +0000},
    Doi = {10.1002/cpe.3908},
    Isbn = {1532-0634},
    Journal = {{Concurrency and Computation: Practice and Experience}},
    Journal1 = {Concurrency Computat.: Pract. Exper.},
    Number = {2},
    Pages = {e3908--n/a},
    Title = {Report on the first workshop on negative and null results in {eScience}},
    Ty = {JOUR},
    Url = {http://dx.doi.org/10.1002/cpe.3908},
    Volume = {29},
    Year = {2017},
    Bdsk-Url-1 = {http://dx.doi.org/10.1002/cpe.3908}}

2016

  • [DOI] A. J. van Altena, P. D. Moerland, A. H. Zwinderman, and S. D. Olabarriaga, “Understanding big data themes from scientific biomedical literature through topic modeling,” Journal of Big Data, vol. 3, iss. 1, p. 23, 2016.
    [Bibtex]
    @article{vanAltena2016,
    Abstract = {Nowadays, big data is a key component in (bio)medical research. However, the meaning of the term is subject to a wide array of opinions, without a formal definition. This hampers communication and leads to missed opportunities. For example, in the (bio)medical field we have observed many different interpretations, some of which have a negative connotation, impeding exploitation of big data approaches. In this paper we pursue a better understanding of the term big data through a data-driven systematic approach using text analysis of scientific (bio)medical literature. We attempt to find how existing big data definitions are expressed within the chosen application domain. We build upon findings of previous qualitative research by De Mauro et al. (Lib Rev 65: 122--135, 14), which analysed fifteen definitions and identified four key big data themes (i.e., information, methods, technology, and impact). We have revisited these and other definitions of big data, and consolidated them into eight additional themes, resulting in a total of twelve themes. The corpus was composed of paper abstracts extracted from (bio)medical literature databases, searching for `big data'. After text pre-processing and parameter selection, topic modelling was applied with 25 topics. The resulting top-20 words per topic were annotated with the twelve big data themes by seven observers. The analysis of these annotations show that the themes proposed by De Mauro et al. are strongly expressed in the corpus. Furthermore, several of the most popular big data V's (i.e., volume, velocity, and value) also have a relatively high presence. Other V's introduced more recently (e.g. variability) were however hardly found in the 25 topics. These findings show that the current understanding of big data within the (bio)medical domain is in agreement with more general definitions of the term.},
    Author = {van Altena, Allard J. and Moerland, Perry D. and Zwinderman, Aeilko H. and Olabarriaga, S{\'\i}lvia D.},
    Date-Added = {2017-02-16 11:18:38 +0000},
    Date-Modified = {2017-02-16 11:18:50 +0000},
    Doi = {10.1186/s40537-016-0057-0},
    Issn = {2196-1115},
    Journal = {{Journal of Big Data}},
    Number = {1},
    Pages = {23},
    Title = {Understanding big data themes from scientific biomedical literature through topic modeling},
    Url = {http://dx.doi.org/10.1186/s40537-016-0057-0},
    Volume = {3},
    Year = {2016},
    Bdsk-Url-1 = {http://dx.doi.org/10.1186/s40537-016-0057-0}}
  • [DOI] R. S. Barros, S. D. Olabarriaga, J. Borst, M. A. A. van Walderveen, J. S. Posthuma, G. J. Streekstra, M. van Herk, C. B. L. M. Majoie, and H. A. Marquering, “Dynamic CT perfusion image data compression for efficient parallel processing,” Medical & Biological Engineering & Computing, vol. 54, iss. 2, pp. 463-473, 2016.
    [Bibtex]
    @article{Barros2016,
    Abstract = {The increasing size of medical imaging data, in particular time series such as CT perfusion (CTP), requires new and fast approaches to deliver timely results for acute care. Cloud architectures based on graphics processing units (GPUs) can provide the processing capacity required for delivering fast results. However, the size of CTP datasets makes transfers to cloud infrastructures time-consuming and therefore not suitable in acute situations. To reduce this transfer time, this work proposes a fast and lossless compression algorithm for CTP data. The algorithm exploits redundancies in the temporal dimension and keeps random read-only access to the image elements directly from the compressed data on the GPU. To the best of our knowledge, this is the first work to present a GPU-ready method for medical image compression with random access to the image elements from the compressed data.},
    Author = {Barros, Renan Sales and Olabarriaga, Silvia Delgado and Borst, Jordi and van Walderveen, Marianne A. A. and Posthuma, Jorrit S. and Streekstra, Geert J. and van Herk, Marcel and Majoie, Charles B. L. M. and Marquering, Henk A.},
    Date-Added = {2016-06-27 08:28:21 +0000},
    Date-Modified = {2016-07-19 08:07:38 +0000},
    Doi = {10.1007/s11517-015-1331-6},
    Issn = {1741-0444},
    Journal = {{Medical {\&} Biological Engineering {\&} Computing}},
    Number = {2},
    Pages = {463--473},
    Title = {{Dynamic CT perfusion image data compression for efficient parallel processing}},
    Url = {http://dx.doi.org/10.1007/s11517-015-1331-6},
    Volume = {54},
    Year = {2016},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/s11517-015-1331-6}}
  • [DOI] M. M. Jaghoori, B. Bleijlevens, and S. D. Olabarriaga, “1001 Ways to run AutoDock Vina for virtual screening,” Journal of Computer-Aided Molecular Design, vol. 30, iss. 3, pp. 237-249, 2016.
    [Bibtex]
    @article{Jaghoori:2016aa,
    Abstract = {Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.},
    Author = {Jaghoori, Mohammad Mahdi and Bleijlevens, Boris and Olabarriaga, Silvia D.},
    Da = {2016//},
    Date-Added = {2016-06-27 08:28:34 +0000},
    Date-Modified = {2016-07-19 08:07:53 +0000},
    Doi = {10.1007/s10822-016-9900-9},
    Id = {Jaghoori2016},
    Isbn = {1573-4951},
    Journal = {{Journal of Computer-Aided Molecular Design}},
    Number = {3},
    Pages = {237--249},
    Title = {{1001 Ways to run AutoDock Vina for virtual screening}},
    Ty = {JOUR},
    Url = {http://dx.doi.org/10.1007/s10822-016-9900-9},
    Volume = {30},
    Year = {2016},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/s10822-016-9900-9}}
  • [DOI] S. D. Olabarriaga and N. Wilkins-Diehr, “GCE15 special issue conference publications,” Concurrency and Computation: Practice and Experience, vol. 28, iss. 7, pp. 1949-1951, 2016.
    [Bibtex]
    @article{CPE:CPE3743,
    Author = {Olabarriaga, Silvia Delgado and Wilkins-Diehr, Nancy},
    Date-Added = {2016-06-27 08:40:02 +0000},
    Date-Modified = {2017-02-16 11:13:36 +0000},
    Doi = {10.1002/cpe.3743},
    Issn = {1532-0634},
    Journal = {{Concurrency and Computation: Practice and Experience}},
    Note = {CPE-15-0507},
    Number = {7},
    Pages = {1949--1951},
    Title = {{GCE15} Special Issue Conference Publications},
    Url = {http://dx.doi.org/10.1002/cpe.3743},
    Volume = {28},
    Year = {2016},
    Bdsk-Url-1 = {http://dx.doi.org/10.1002/cpe.3743}}
  • G. Pierantoni, D. Frost, S. Gesing, S. Olabarriaga, G. Tertyansky, M. Jaghoori, and J. Arshad, “A model for information and action flows connecting science gateways to distributed computing infrastructures,” in Science Gateways (IWSG), 2016 8th International Workshop on, Rome, 2016.
    [Bibtex]
    @inproceedings{Gab2016,
    Address = {Rome},
    Author = {Gabriele Pierantoni and Dermot Frost and Sandra Gesing and Silvia Olabarriaga and Gabor Tertyansky and Mahdi Jaghoori and Junaid Arshad},
    Booktitle = {{Science Gateways (IWSG), 2016 8th International Workshop on}},
    Date-Added = {2016-06-27 08:44:05 +0000},
    Date-Modified = {2016-07-19 08:08:12 +0000},
    Month = {June},
    Title = {A Model for Information and Action Flows Connecting Science Gateways to Distributed Computing Infrastructures},
    Year = {2016}}
  • S. Shahand and S. D. Olabarriaga, “Rosemary: A Flexible Programming Framework to Build Science Gateways,” in Science Gateways (IWSG), 2016 8th International Workshop on, Rome, 2016.
    [Bibtex]
    @inproceedings{Shahan2016,
    Address = {Rome},
    Author = {Shahand, Shayan and Olabarriaga, Silvia D},
    Booktitle = {{Science Gateways (IWSG), 2016 8th International Workshop on}},
    Date-Added = {2016-06-27 08:41:16 +0000},
    Date-Modified = {2016-07-19 08:08:05 +0000},
    Month = {June},
    Title = {{Rosemary: A Flexible Programming Framework to Build Science Gateways}},
    Year = {2016}}

2015

  • [DOI] R. S. Barros, J. Borst, S. Kleynenberg, C. Badr, R. Ganji, H. de Bliek, L. Zeng-Eyindanga, H. van den Brink, C. Majoie, H. Marquering, and S. D. Olabarriaga, “Remote Collaboration, Decision Support, and On-Demand Medical Image Analysis for Acute Stroke Care,” in Service Oriented and Cloud Computing: 4th European Conference, ESOCC 2015, Taormina, Italy, September 15-17, 2015, Proceedings, Cham, 2015, pp. 214-225.
    [Bibtex]
    @inproceedings{Barros2015,
    Address = {Cham},
    Author = {Barros, Renan Sales and Borst, Jordi and Kleynenberg, Steven and Badr, C{\'e}line and Ganji, Rama-Rao and de Bliek, Hubrecht and Zeng-Eyindanga, Landry-St{\'e}phane and van den Brink, Henk and Majoie, Charles and Marquering, Henk and Olabarriaga, S{\'\i}lvia Delgado},
    Booktitle = {{Service Oriented and Cloud Computing: 4th European Conference, ESOCC 2015, Taormina, Italy, September 15-17, 2015, Proceedings}},
    Date-Added = {2016-06-27 08:33:29 +0000},
    Date-Modified = {2016-07-19 08:05:54 +0000},
    Doi = {10.1007/978-3-319-24072-5_15},
    Editor = {Dustdar, Schahram and Leymann, Frank and Villari, Massimo},
    Isbn = {978-3-319-24072-5},
    Pages = {214--225},
    Publisher = {Springer International Publishing},
    Title = {{Remote Collaboration, Decision Support, and On-Demand Medical Image Analysis for Acute Stroke Care}},
    Url = {http://dx.doi.org/10.1007/978-3-319-24072-5_15},
    Year = {2015},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/978-3-319-24072-5_15},
    Bdsk-File-1 = {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}}
  • M. Caan, J. Teeuw, S. Shahand, M. M. Jaghoori, J. Huguet, A. van Altena, and S. D. Olabarriaga, “A neuroscience gateway for handling and processing population imaging studies,” in Proceedings of the 1st Miccai 2015 Workshop on Management and Processing of images for Population Imaging (MICCAI MAPPING 2015), 2015, pp. 15-22.
    [Bibtex]
    @inproceedings{caan2015,
    Author = {Caan, Matthan and Teeuw, Jalmar and Shahand, Shayan and Jaghoori, Mohammad Mahdi and Huguet, Jordi and van Altena, Allard and Olabarriaga, Silvia D},
    Booktitle = {{Proceedings of the 1st Miccai 2015 Workshop on Management and Processing of images for Population Imaging (MICCAI MAPPING 2015)}},
    Date-Modified = {2016-07-19 08:06:46 +0000},
    Organization = {MICCAI},
    Pages = {15-22},
    Title = {A neuroscience gateway for handling and processing population imaging studies},
    Url = {https://project.inria.fr/fli/en/mapping-workshop/},
    Year = {2015},
    Bdsk-Url-1 = {https://project.inria.fr/fli/en/mapping-workshop/}}
  • [DOI] M. M. Jaghoori, A. J. van Altena, B. Bleijlevens, S. Ramezani, J. L. Font, and S. D. Olabarriaga, “A multi-infrastructure gateway for virtual drug screening,” Concurrency and Computation: Practice and Experience, p. n/a–n/a, 2015.
    [Bibtex]
    @article{CPE:CPE3498,
    Author = {Jaghoori, Mohammad Mahdi and van Altena, Allard J. and Bleijlevens, Boris and Ramezani, Sara and Font, Juan Luis and Olabarriaga, Silvia D.},
    Date-Modified = {2016-07-19 08:06:55 +0000},
    Doi = {10.1002/cpe.3498},
    Issn = {1532-0634},
    Journal = {{Concurrency and Computation: Practice and Experience}},
    Keywords = {science gateway, eScience, drug discovery, virtual screening, grid computing, Hadoop},
    Pages = {n/a--n/a},
    Title = {A multi-infrastructure gateway for virtual drug screening},
    Url = {http://dx.doi.org/10.1002/cpe.3498},
    Year = {2015},
    Bdsk-Url-1 = {http://dx.doi.org/10.1002/cpe.3498}}
  • [DOI] M. M. Jaghoori, S. Shahand, and S. D. Olabarriaga, “Processing manager for science gateways,” in Science Gateways (IWSG), 2015 7th International Workshop on, 2015, pp. 1-7.
    [Bibtex]
    @inproceedings{7217921,
    Author = {M. M. Jaghoori and S. Shahand and S. D. Olabarriaga},
    Booktitle = {{Science Gateways (IWSG), 2015 7th International Workshop on}},
    Date-Added = {2016-06-27 08:36:54 +0000},
    Date-Modified = {2016-07-19 08:07:10 +0000},
    Doi = {10.1109/IWSG.2015.9},
    Keywords = {data analysis;network servers;scientific information systems;data consumption;data services;domain level processing;external high-level control;heterogeneous execution platforms;homogeneous abstraction layer;infrastructure level processing;necessary management layer;processing manager;science gateways;scientific application execution;scientific domain;software layer;Computer architecture;Logic gates;Monitoring;Process control;Servers;Software;Distributed Computing;Provenance;Science Gateways;Separation of Concerns;Software Engineering;eScience},
    Month = {June},
    Pages = {1-7},
    Title = {Processing Manager for Science Gateways},
    Year = {2015},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/IWSG.2015.9}}
  • R. Sales Barros, E. Bennink, J. Posthuma, J. Oosterbroek, C. Majoie, H. de Jong, S. Olabarriaga, and H. Marquering, “High Performance Analysis of Compressed Dynamic CT Perfusion Image Data for Acute Care of Ischemic Stroke,” in 8th International Workshop on High Performance Computing for Biomedical Image Analysis (HPC-MICCAI), 2015.
    [Bibtex]
    @inproceedings{barros2015b,
    Author = {Sales Barros, Renan and Bennink, Edwin and Posthuma, Jorrit and Oosterbroek, Jaap and Majoie, Charles and de Jong, Hugo and Olabarriaga, Silvia and Marquering, Henk},
    Booktitle = {{8th International Workshop on High Performance Computing for Biomedical Image Analysis (HPC-MICCAI)}},
    Date-Modified = {2016-07-19 08:06:34 +0000},
    Note = {to appear},
    Organization = {MICCAI},
    Title = {{High Performance Analysis of Compressed Dynamic CT Perfusion Image Data for Acute Care of Ischemic Stroke}},
    Year = {2015}}
  • [DOI] S. Shahand, A. H. C. van Kampen, and S. D. Olabarriaga, “Science Gateway Canvas: A business reference model for Science Gateways,” in Proceedings of the Science of Cyberinfrastructure: Research, Experience, Applications and Models, Portland, OR, USA, 2015.
    [Bibtex]
    @inproceedings{shahand:2015ab,
    Address = {Portland, OR, USA},
    Author = {Shahand, Shayan and van Kampen, Antoine H. C. and Olabarriaga, S\'{\i}lvia D.},
    Booktitle = {{Proceedings of the Science of Cyberinfrastructure: Research, Experience, Applications and Models}},
    Doi = {10.1145/2753524.2753527},
    Series = {SCREAM'15},
    Title = {{Science Gateway Canvas: A business reference model for Science Gateways}},
    Url = {http://dx.doi.org/10.1145/2753524.2753527},
    Year = {2015},
    Bdsk-Url-1 = {http://dx.doi.org/10.1145/2753524.2753527}}
  • [DOI] S. Shahand, A. Benabdelkader, M. M. Jaghoori, M. al Mourabit, J. Huguet, M. W. A. Caan, A. H. C. van Kampen, and S. D. Olabarriaga, “A Data-centric Neuroscience Gateway: Design, Implementation, and Experiences,” Concurrency and Computation: Practice and Experience, vol. 27, iss. 2, pp. 489-506, 2015.
    [Bibtex]
    @article{shahand:2015aa,
    Abstract = {Science gateways provide UIs and high-level services to access and manage applications and data collections on distributed resources. They facilitate users to perform data analysis on distributed computing infrastructures without getting involved into the technical details. The e-BioInfra Gateway is a science gateway for biomedical data analysis on a national grid infrastructure, which has been successfully adopted for neuroscience research. This paper describes the motivation, requirements, and design of a new generation of e-BioInfra Gateway, which is based on the grid and cloud user support environment (also known as WS-PGRADE/gUSE framework) and supports heterogeneous infrastructures. The new gateway has been designed to have additional data and meta-data management facilities to access and manage (biomedical) data servers, and to provide data-centric user interaction. We have implemented and deployed the new gateway for the computational neuroscience research community of the Academic Medical Center of the University of Amsterdam. This paper presents the system architecture of the new gateway, highlights the improvements that have been achieved, discusses the choices that we have made, and reflects on those based on initial user feedback. Copyright {\copyright} 2014 John Wiley & Sons, Ltd.},
    Author = {Shahand, Shayan and Benabdelkader, Ammar and Jaghoori, Mohammad Mahdi and Mourabit, Mostapha al and Huguet, Jordi and Caan, Matthan W.A. and van Kampen, Antoine H.C. and Olabarriaga, S{\'\i}lvia D.},
    Date-Modified = {2016-07-19 08:07:01 +0000},
    Doi = {10.1002/cpe.3281},
    Issn = {1532-0634},
    Journal = {{Concurrency and Computation: Practice and Experience}},
    Keywords = {science gateway (SG), e-Science, computational neuroscience, medical image analysis, grid computing, virtual laboratory (VL), problem solving environment (PSE), virtual research enviroment (VRE)},
    Number = {2},
    Pages = {489--506},
    Title = {{A Data-centric Neuroscience Gateway: Design, Implementation, and Experiences}},
    Url = {http://dx.doi.org/10.1002/cpe.3281},
    Volume = {27},
    Year = {2015},
    Bdsk-Url-1 = {http://dx.doi.org/10.1002/cpe.3281}}
  • [DOI] S. Shahand, J. van Duffelen, and S. D. Olabarriaga, “Reflections on science gateways sustainability through the business model canvas: case study of a neuroscience gateway,” Concurrency and Computation: Practice and Experience, p. n/a–n/a, 2015.
    [Bibtex]
    @article{shahand:2015ac,
    Abstract = {The sustainability of science gateways has been a topic of active discussion because they have been created and supported in the context of temporary research and infrastructure projects. As successful projects come to an end, it is necessary to find (new) models to secure continuous exploitation of products generated by these projects. Taking this step requires business considerations that are not trivial to do from the role of a researcher. This paper presents our experiences in adopting a methodology from lean business development, the Business Model Canvas (BMC). This methodology enables structured reflection upon the business model and facilitates exploring alternative ones (pivoting). We have applied the BMC to one of the science gateways designed, developed, and operated by the Academic Medical Center (AMC) e-Science group: the AMC Computational Neuroscience Gateway. The current gateway BMC is explained in the paper and used as basis for a reflection to improve its sustainability. Alternative business models are given as examples of BMC iteration or pivots. This exercise helped us to structure the various aspects to be considered when designing or reflecting upon the business model of our gateway. It also facilitated the visualization of the complete business picture and helps the reflection about improvements in the business model toward sustainability. We believe that this methodology could be valuable also for the reflection about sustainability of other science gateways that are growing from academic groups that do not have business training. Copyright {\copyright} 2015 John Wiley & Sons, Ltd.},
    Author = {Shahand, S. and van Duffelen, J. and Olabarriaga, S. D.},
    Date-Modified = {2016-07-19 08:06:08 +0000},
    Doi = {10.1002/cpe.3524},
    Issn = {1532-0634},
    Journal = {{Concurrency and Computation: Practice and Experience}},
    Keywords = {science gateway (SG), virtual research environment (VRE), Business Model Canvas (BMC), sustainability},
    Pages = {n/a--n/a},
    Title = {Reflections on science gateways sustainability through the business model canvas: case study of a neuroscience gateway},
    Url = {http://dx.doi.org/10.1002/cpe.3524},
    Year = {2015},
    Bdsk-Url-1 = {http://dx.doi.org/10.1002/cpe.3524}}
  • [DOI] J. Teeuw, M. W. A. Caan, and S. D. Olabarriaga, “Robust Automated White Matter Pathway Reconstruction for Large Studies,” in Medical Image Computing and Computer-Assisted Intervention — MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part I, Cham, 2015, pp. 101-108.
    [Bibtex]
    @inproceedings{Teeuw2015,
    Address = {Cham},
    Author = {Teeuw, Jalmar and Caan, Matthan W. A. and Olabarriaga, Silvia D.},
    Booktitle = {{Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part I}},
    Date-Added = {2016-06-27 08:32:37 +0000},
    Date-Modified = {2016-07-19 08:05:33 +0000},
    Doi = {10.1007/978-3-319-24553-9_13},
    Editor = {Navab, Nassir and Hornegger, Joachim and Wells, M. William and Frangi, F. Alejandro},
    Isbn = {978-3-319-24553-9},
    Pages = {101--108},
    Publisher = {Springer International Publishing},
    Title = {{Robust Automated White Matter Pathway Reconstruction for Large Studies}},
    Url = {http://dx.doi.org/10.1007/978-3-319-24553-9_13},
    Year = {2015},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/978-3-319-24553-9_13}}

2014

  • [DOI] A. W. G. Buijink, M. W. A. Caan, F. M. Contarino, R. P. Schuurman, P. van den Munckhof, R. M. A. de Bie, S. Olabarriaga, J. D. Speelman, and A. F. van Rootselaar, “Structural changes in cerebellar outflow tracts after thalamotomy in essential tremor,” PARKINSONISM & RELATED DISORDERS, vol. 20, iss. 5, pp. 554-7, 2014.
    [Bibtex]
    @article{Buijink,
    Abstract = {BACKGROUND:
    This study set out to determine whether structural changes are present outside the thalamus after thalamotomy in patients with essential tremor (ET), specifically in the cerebellorubrothalamic tracts. We hypothesized that diffusion tensor imaging (DTI) would detect these changes.
    METHODS:
    We collected DTI scans and analyzed differences in Fractional Anisotropy (FA) and Mean Diffusivity (MD) between the left and right superior and middle cerebellar peduncle in ET patients that have undergone unilateral, left, thalamotomy and ET patients that did not undergo thalamotomy (control group). We used classical ROI-based statistics to determine whether changes are present.
    RESULTS:
    We found decreased FA and increased MD values in the right superior cerebellar peduncle leading to the left, lesioned thalamus, only in the thalamotomy group.
    CONCLUSIONS:
    Our study suggests long-term structural changes in the cerebellorubrothalamic tract after thalamotomy. This contributes to further understanding of the biological mechanism following surgical lesions in the basal ganglia.},
    Author = {Buijink, Arthur W. G. and Caan, Matthan W. A. and Contarino, M. Fiorella and Schuurman, P. Richard and van den Munckhof, Pepijn and de Bie, Rob M. A. and Olabarriaga, Silvia and Speelman, Johannes D. and van Rootselaar, Anne Fleur},
    Date-Modified = {2016-07-19 08:10:30 +0000},
    Doi = {10.1016/j.parkreldis.2014.02.020},
    Journal = {{PARKINSONISM & RELATED DISORDERS}},
    Number = {5},
    Pages = {554-7},
    Title = {Structural changes in cerebellar outflow tracts after thalamotomy in essential tremor},
    Volume = {20},
    Year = {2014},
    Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.parkreldis.2014.02.020}}
  • [DOI] M. M. Jaghoori, S. Ramezani, and S. D. Olabarriaga, “User-oriented Partial Result Evaluation in Workflow-based Science Gateways,” in Proceedings of the 9th Workshop on Workflows in Support of Large-Scale Science, Piscataway, NJ, USA, 2014, pp. 70-81.
    [Bibtex]
    @inproceedings{Jaghoori:2014:UPR:2691175.2691186,
    Abstract = {Scientific workflow management systems provide a useful layer for defining and executing applications supported by science gateways. In various optimization or simulation applications that need to run for a long time, the users may be satisfied with an incomplete execution. The system should, therefore, allow users to evaluate partial results of the workflow execution. This entails performing a consolidation step, that would normally run only at the end of the workflow. In this paper, we present two new workflow patterns that formally define how the consolidation step should be executed (on partial inputs) whenever the user pro-actively requests evaluation of the partial results. This changes the traditional workflow behavior, in which every step runs once, when all its data dependencies are satisfied. We evaluate implementing these patterns in various workflow management systems and finally present a DIRAC-based implementation of this feature for the use case of a molecular docking gateway.},
    Address = {Piscataway, NJ, USA},
    Author = {Jaghoori, Mohammad Mahdi and Ramezani, Sara and Olabarriaga, Silvia D.},
    Booktitle = {{Proceedings of the 9th Workshop on Workflows in Support of Large-Scale Science}},
    Date-Modified = {2016-07-19 08:10:42 +0000},
    Doi = {10.1109/WORKS.2014.7},
    Pages = {70--81},
    Publisher = {IEEE Press},
    Series = {WORKS '14},
    Title = {{User-oriented Partial Result Evaluation in Workflow-based Science Gateways}},
    Year = {2014},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/WORKS.2014.7}}
  • M. M. Jaghoori, A. V. J. Altena, B. Bleijlevens, and S. D. Olabarriaga, “A Grid-Enabled Virtual Screening Gateway,” in Science Gateways (IWSG), 2014 6th International Workshop on, 2014, pp. 24-29.
    [Bibtex]
    @inproceedings{jaghoori2014grid,
    Author = {Jaghoori, Mohammad Mahdi and Altena, Allard J Van and Bleijlevens, Boris and Olabarriaga, Silvia D},
    Booktitle = {{Science Gateways (IWSG), 2014 6th International Workshop on}},
    Date-Modified = {2016-07-19 08:08:38 +0000},
    Organization = {IEEE},
    Pages = {24--29},
    Title = {{A Grid-Enabled Virtual Screening Gateway}},
    Year = {2014}}
  • [DOI] S. D. Olabarriaga, A. Benabdelkader, M. W. A. Caan, M. M. Jaghoori, J. Krüger, L. de la Garza, C. Mohr, B. Schubert, A. Danezi, and T. Kiss, “WS-PGRADE/gUSE-Based Science Gateways in Teaching,” in Science Gateways for Distributed Computing Infrastructures, P. Kacsuk, Ed., Springer International Publishing, 2014, pp. 223-234.
    [Bibtex]
    @incollection{olabarriaga,
    Abstract = {Various WS-PGRADE/gUSE science gateways have been extensively used in educational contexts, supporting courses offered by different European universities and organizations. This chapter presents some examples of how WS-PGRADE/gUSE generic and customized gateways have been used in such courses. These examples include practical cases from a variety of scientific fields and educational styles. For each case, the educational context and the course organization are presented, with emphasis on how the respective portal has been adopted for the practical exercises. A summary of experiences are also reported, including advantages and difficulties faced for using these gateways in teaching.},
    Author = {Olabarriaga, S{\'\i}lvia D. and Benabdelkader, Ammar and Caan, Matthan W.A. and Jaghoori, Mohammad Mahdi and Kr{\"u}ger, Jens and de la Garza, Luis and Mohr, Christopher and Schubert, Benjamin and Danezi, Anatoli and Kiss, Tamas},
    Booktitle = {{Science Gateways for Distributed Computing Infrastructures}},
    Date-Modified = {2016-07-19 08:10:53 +0000},
    Doi = {10.1007/978-3-319-11268-8_16},
    Editor = {Kacsuk, P{\'e}ter},
    Pages = {223-234},
    Publisher = {Springer International Publishing},
    Title = {{WS-PGRADE/gUSE-Based Science Gateways in Teaching}},
    Year = {2014},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/978-3-319-11268-8_16}}
  • S. Olabarriaga, G. Pierantoni, G. Taffoni, E. Sciacca, M. Jaghoori, V. Korkhov, G. Castelli, C. Vuerli, U. Becciani, E. Carley, and others, “Scientific workflow management–for whom?,” in e-Science (e-Science), 2014 IEEE 10th International Conference on, 2014, pp. 298-305.
    [Bibtex]
    @inproceedings{olabarriaga2014scientific,
    Author = {Olabarriaga, Silvia and Pierantoni, Gabrielle and Taffoni, Giuliano and Sciacca, Eva and Jaghoori, Mahdi and Korkhov, Vladimir and Castelli, Giuliano and Vuerli, Claudio and Becciani, Ugo and Carley, Eoin and others},
    Booktitle = {{e-Science (e-Science), 2014 IEEE 10th International Conference on}},
    Date-Modified = {2016-07-19 08:10:12 +0000},
    Organization = {IEEE},
    Pages = {298--305},
    Title = {Scientific Workflow Management--For Whom?},
    Year = {2014}}
  • [DOI] R. Sales Barros, S. van Geldermalsen, A. M. M. Boers, A. Belloum, H. A. Marquering, and S. Olabarriaga, “Heterogeneous platform programming for high performance medical imaging processing,” in Euro-Par 2013: Parallel Processing Workshops, D. an Mey, M. Alexander, P. Bientinesi, M. Cannataro, C. Clauss, A. Costan, G. Kecskemeti, C. Morin, L. Ricci, J. Sahuquillo, M. Schulz, V. Scarano, S. Scott, and J. Weidendorfer, Eds., Springer Berlin Heidelberg, 2014, vol. 8374, pp. 301-310.
    [Bibtex]
    @incollection{Barros:2014aa,
    Abstract = {Medical imaging processing algorithms can be computationally very demanding. Currently, computers with multiple computing devices, such as multi-core CPUs, GPUs, and FPGAs, have emerged as powerful processing environments. These so called heterogeneous platforms have potential to significantly accelerate medical imaging applications. In this study, we evaluate the potential of heterogeneous platforms to improve the processing speed of medical imaging applications by using a new framework named FlowCL. This framework facilitates the development of parallel applications for heterogeneous platforms. We compared an implementation of region growing based method to automated cerebral infarct volume measurement with a new implementation targeted for heterogeneous platforms. The results of this new implementation agree well with the original implementation and they are obtained with significant speed-up comparing to the sequential implementation.},
    Author = {Sales Barros, Renan and van Geldermalsen, Sytse and Boers, Anna M.M. and Belloum, AdamS.Z. and Marquering, Henk A. and Olabarriaga, Silvia},
    Booktitle = {{Euro-Par 2013: Parallel Processing Workshops}},
    Date-Modified = {2016-07-19 08:09:52 +0000},
    Doi = {10.1007/978-3-642-54420-0_30},
    Editor = {an Mey, Dieter and Alexander, Michael and Bientinesi, Paolo and Cannataro, Mario and Clauss, Carsten and Costan, Alexandru and Kecskemeti, Gabor and Morin, Christine and Ricci, Laura and Sahuquillo, Julio and Schulz, Martin and Scarano, Vittorio and Scott, StephenL. and Weidendorfer, Josef},
    Pages = {301-310},
    Publisher = {Springer Berlin Heidelberg},
    Series = {Lecture Notes in Computer Science},
    Title = {Heterogeneous Platform Programming for High Performance Medical Imaging Processing},
    Volume = {8374},
    Year = {2014},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/978-3-642-54420-0_30}}
  • [DOI] S. Shahand, M. Jaghoori, A. Benabdelkader, J. Font-Calvo, J. Huguet, M. Caan, A. van Kampen, and S. Olabarriaga, “Computational Neuroscience Gateway: A Science Gateway Based on the WS-PGRADE/gUSE,” in Science Gateways for Distributed Computing Infrastructures, P. Kacsuk, Ed., Springer International Publishing, 2014, pp. 139-149.
    [Bibtex]
    @incollection{shahand:2014ac,
    Abstract = {Computational neuroscientists face challenges to manage ever-increasing large volume of data and to process them with applications that require great computational power. The Brain Imaging Centre of the Academic Medical Centre of the University of Amsterdam is a community of neuroscientists who are involved in various computational neuroscience research studies. They face various challenges to process and manage a growing amount of neuroimaging data. The goal of the computational neuroscience gateway is to facilitate large-scale data processing on distributed infrastructures and to enhance data management and collaboration for scientific research. The gateway is based on the WS-PGRADE/gUSE generic science gateway framework as platform for distributed computing, and it is connected to a data server based on the eXtensible Neuroimaging Archive Toolkit (XNAT). This chapter presents the design and architecture of the gateway with focus on the utilization of the WS-PGRADE/gUSE framework, and the lessons learned during its implementation and operation.},
    Author = {Shahand, Shayan and Jaghoori, MohammadMahdi and Benabdelkader, Ammar and Font-Calvo, JuanLuis and Huguet, Jordi and Caan, MatthanW.A. and van Kampen, AntoineH.C. and Olabarriaga, S{\'\i}lviaD.},
    Booktitle = {{Science Gateways for Distributed Computing Infrastructures}},
    Date-Modified = {2016-07-19 08:09:42 +0000},
    Doi = {10.1007/978-3-319-11268-8_10},
    Editor = {Kacsuk, P{\'e}ter},
    Pages = {139-149},
    Publisher = {Springer International Publishing},
    Title = {{Computational Neuroscience Gateway: A Science Gateway Based on the WS-PGRADE/gUSE}},
    Year = {2014},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/978-3-319-11268-8_10}}
  • [DOI] S. Shahand and S. D. Olabarriaga, “Initial steps in analyzing science gateways sustainability through business model canvas: a use case for the computational neuroscience gateway,” in Proceedings of the 9th Gateway Computing Environments Workshop, Piscataway, NJ, USA, 2014, pp. 5-8.
    [Bibtex]
    @inproceedings{shahand:2014ab,
    Abstract = {The sustainability of science gateways has been a topic of active discussion. As successful research projects come to an end, it is necessary to find (new) models to secure continuous exploitation of products generated by these projects. Taking this step requires business considerations that are not trivial to do from the role of a researcher. In this paper we present our experiences in adopting the Business Model Canvas (BMC) methodology to reflect upon the sustainability of the science gateways designed, developed and operated by our group. This experience shows that the BMC helps to structure the various aspects to be considered, provides an excellent overview, and facilitates exploring alternative business models. We believe that this tool could be valuable also for other small groups that are facing similar challenges.},
    Address = {Piscataway, NJ, USA},
    Author = {Shahand, Shayan and Olabarriaga, S\'{\i}lvia D.},
    Booktitle = {{Proceedings of the 9th Gateway Computing Environments Workshop}},
    Date-Modified = {2016-07-19 08:10:04 +0000},
    Doi = {10.1109/GCE.2014.16},
    Pages = {5--8},
    Publisher = {IEEE Press},
    Series = {GCE '14},
    Title = {Initial Steps in Analyzing Science Gateways Sustainability Through Business Model Canvas: A Use Case for the Computational Neuroscience Gateway},
    Year = {2014},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/GCE.2014.16}}

2013

  • [DOI] Z. Farkas, P. Kacsuk, A. Balasko, K. Karoczkai, M. Santcroos, and S. D. Olabarriaga, “Data bridge: solving diverse data access in scientific applications,” in Proceedings of 5th International Workshop on Science Gateways (IWSG), 2013.
    [Bibtex]
    @inproceedings{Farkas,
    Abstract = {The nature of data for scientific computation is
    very diverse in the age of big data. First, it may be available
    at a number of locations, e.g. the scientist's machine, some
    institutional filesystem, a remote service, or some sort of database.
    Second, the size of the data may vary from a few kilobytes
    to many terabytes. In order to be available for computation,
    data has to be transferred to the location where the computation
    takes place. This requires a diverse set of middleware tools that
    are compatible both with the data and the compute resources.
    However, using this tools requires additional knowledge and
    makes running the experiments an inconvenient task. In this
    paper we present the Data Bridge, a high-level service that can
    be used easily in scientific computations to perform data transfer
    to and from a diverse set of storage services. The Data Bridge
    not only unifies access to different types of storage services, but
    it can also be used at different levels (e.g., single jobs, parameter
    sweeps, scientific workflows) in scientific computations.},
    Author = {Farkas, Zoltan and Kacsuk, Peter and Balasko, Akos and Karoczkai, Krisztian and Santcroos, Mark and Olabarriaga, S. D.},
    Booktitle = {{Proceedings of 5th International Workshop on Science Gateways (IWSG)}},
    Date-Modified = {2016-07-19 08:11:45 +0000},
    Doi = {http://ceur-ws.org/Vol-993/paper12.pdf},
    Title = {Data Bridge: solving diverse data access in scientific applications},
    Year = {2013},
    Bdsk-Url-1 = {http://ceur-ws.org/Vol-993/paper12.pdf}}
  • [DOI] V. Korkhov, D. Krefting, T. Kukla, G. Z. Terstyanszky, M. W. A. Caan, and S. D. Olabarriaga, “Exploring Workflow Interoperability for Neuroimage Analysis on the SHIWA Platform,” Journal of Grid Computing, vol. 11, iss. 3, pp. 505-522, 2013.
    [Bibtex]
    @article{Korkhov,
    Author = {Korkhov, Vladimir and Krefting, Dagmar and Kukla, Tamas and Terstyanszky, Gabor Z. and Caan, Matthan W.A. and Olabarriaga, S.D.},
    Date-Modified = {2016-07-19 08:12:22 +0000},
    Doi = {10.1007/s10723-013-9262-7},
    Journal = {{Journal of Grid Computing}},
    Number = {3},
    Pages = {505-522},
    Title = {{Exploring Workflow Interoperability for Neuroimage Analysis on the SHIWA Platform}},
    Volume = {11},
    Year = {2013},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/s10723-013-9262-7}}
  • [DOI] B. de Kwaasteniet, E. Ruhe, M. Caan, M. Rive, S. Olabarriaga, M. Groefsema, L. Heesink, G. van Wingen, and D. Denys, “Relation between structural and functional connectivity in major depressive disorder,” Biological Psychiatry, vol. 74, iss. 1, pp. 40-47, 2013.
    [Bibtex]
    @article{kwaasteniet:2013aa,
    Abstract = {BackgroundMajor depressive disorder (MDD) is characterized by abnormalities in both brain structure and function within a frontolimbic network. However, little is known about the relation between structural and functional abnormalities in MDD. Here, we used a multimodal neuroimaging approach to investigate the relation between structural connectivity and functional connectivity within the frontolimbic network.},
    Author = {Bart de Kwaasteniet and Eric Ruhe and Matthan Caan and Maaike Rive and Silvia Olabarriaga and Martine Groefsema and Lieke Heesink and Guido van Wingen and Damiaan Denys},
    Date-Modified = {2016-07-19 08:12:46 +0000},
    Doi = {10.1016/j.biopsych.2012.12.024},
    Journal = {{Biological Psychiatry}},
    Number = {1},
    Pages = {40 - 47},
    Title = {Relation Between Structural and Functional Connectivity in Major Depressive Disorder},
    Volume = {74},
    Year = {2013},
    Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.biopsych.2012.12.024}}
  • [DOI] S. Madougou, S. Shahand, M. Santcroos, B. van Schaik, A. Benabdelkader, A. van Kampen, and S. Olabarriaga, “Characterizing workflow-based activity on a production e-infrastructure using provenance data,” Future Generation Computer Systems, vol. 29, iss. 8, pp. 1931-1942, 2013.
    [Bibtex]
    @article{madougou:2013aa,
    Abstract = {Abstract Grid computing and workflow management systems emerged as solutions to the challenges arising from the processing and storage of shear volumes of data generated by modern simulations and data acquisition devices. Workflow management systems usually document the process of the workflow execution either as structured provenance information or as log files. Provenance is recognized as an important feature in workflow management systems, however there are still few reports on its usage in practical cases. In this paper we present the provenance system implemented in our platform, and then use the information captured by this system during 8 months of platform operation to analyze the platform usage and to perform multilevel error pattern analysis. We make use of the large amount of structured data using the explanatory potential of statistical approaches to find properties of workflows, jobs and resources that are related to workflow failure. Such an analysis enables us to characterize workflow executions on the infrastructure and understand workflow failures. The approach is generic and applicable to other e-infrastructures to gain insight into operational incidents. },
    Author = {Souley Madougou and Shayan Shahand and Mark Santcroos and Barbera van Schaik and Ammar Benabdelkader and Antoine van Kampen and Silvia Olabarriaga},
    Date-Modified = {2016-07-19 08:11:31 +0000},
    Doi = {10.1016/j.future.2013.04.019},
    Journal = {{Future Generation Computer Systems}},
    Number = {8},
    Pages = {1931 - 1942},
    Title = {Characterizing workflow-based activity on a production e-infrastructure using provenance data},
    Volume = {29},
    Year = {2013},
    Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.future.2013.04.019}}
  • [DOI] E. Mouw, G. Van ‘T Noordende, B. Louter, and S. D. Olabarriaga, “A model-based information security risk assessment method for science gateways,” in Proceedings of International 5th Workshop on Science Gateways (IWSG), 2013.
    [Bibtex]
    @inproceedings{Mouw,
    Abstract = {BACKGROUND: Information Security is important
    for e-Science research groups and other small organisations
    that design and operate science gateways and virtual research
    environments, especially when such environments are being used
    for (bio)medical research. We propose a novel method to do risk
    assessments: MISRAM, the Model-based Information Security
    Risk Assessment Method. It uses an information architecture
    model, a method to assign values to information assets and IT
    components, and a method to calculate risks. The output of
    MISRAM is a ranked list of risks and a list of actionable tasks
    to solve the main issues.
    METHODS: MISRAM was applied as a test case to an eScience
    research group at a Dutch research hospital. Meetings
    and surveys were used to create and evaluate lists of information
    assets and IT components. One meeting was used to create a list
    of practical task recommendations.
    RESULTS: Good insight into the information architecture
    and security problems of the IT infrastructure was gained. Also
    the participating group members confirmed that the identified
    security issues were realistic.
    CONCLUSIONS: Our approach raises awareness about security
    among the developers and operators of e-Science environments.
    It also gives insight in how the technical architecture
    affects information security. Traditional questionnaires are an
    important part of any risk assessment, and MISRAM's inclusion
    of such generic questionnaires is an important aspect to create
    an integrated information security risk assessment.},
    Author = {Mouw, Evert and Van 'T Noordende, Guido and Louter, B. and Olabarriaga, S. D.},
    Booktitle = {{Proceedings of International 5th Workshop on Science Gateways (IWSG)}},
    Date-Modified = {2016-07-19 08:11:14 +0000},
    Doi = {http://ceur-ws.org/Vol-993/paper15.pdf},
    Title = {A Model-based Information Security Risk Assessment method for Science Gateways},
    Year = {2013},
    Bdsk-Url-1 = {http://ceur-ws.org/Vol-993/paper15.pdf}}
  • [DOI] S. D. Olabarriaga, M. M. Jaghoori, V. Korkhov, B. van Schaik, and A. van Kampen, “Understanding workflows for distributed computing: nitty-gritty details,” in Proceedings of the 8th Workshop on Workflows in Support of Large-Scale Science, New York, NY, USA, 2013, pp. 68-76.
    [Bibtex]
    @inproceedings{Olabarriaga:2013:UWD:2534248.2534255,
    Abstract = {Scientific workflow management is heavily used in our organization. After six years, a large number of workflows are available and regularly used to run biomedical data analysis experiments on distributed infrastructures, mostly on grids. In this paper we present our first efforts to better understand and characterise these workflows. We start with a set of considerations previously proposed in the literature (workflow dimensions and motifs), and revise these to more closely describe what we observe in our workflows. We conclude that workflow characteristics can be categorized at two levels: firstly, the features characterizing the distributed application and how to implement it as a workflow, and secondly, workflow motifs that depend on the features of the selected workflow management system. These characteristics could be useful in the future to understand a larger set of workflows and to identify functional requirements for further development workflow management systems.},
    Address = {New York, NY, USA},
    Author = {Olabarriaga, Silvia D. and Jaghoori, Mohammad Mahdi and Korkhov, Vladimir and van Schaik, Barbera and van Kampen, Antoine},
    Booktitle = {{Proceedings of the 8th Workshop on Workflows in Support of Large-Scale Science}},
    Date-Modified = {2016-07-19 08:13:16 +0000},
    Doi = {10.1145/2534248.2534255},
    Pages = {68--76},
    Publisher = {ACM},
    Series = {WORKS '13},
    Title = {Understanding Workflows for Distributed Computing: Nitty-gritty Details},
    Year = {2013},
    Bdsk-Url-1 = {http://dx.doi.org/10.1145/2534248.2534255}}
  • B. D. Peters, M. W. J. Machielsen, W. P. Hoen, M. W. A. Caan, A. K. Malhotra, P. R. Szeszko, M. Duran, S. D. Olabarriaga, and L. de Haan, “Polyunsaturated fatty acid concentration predicts myelin integrity in early-phase psychosis,” Schizophrenia Bulletin, vol. 39, iss. 4, pp. 830-838, 2013.
    [Bibtex]
    @article{peters:2013aa,
    Author = {Peters, Bart D. and Machielsen, Marise W. J. and Hoen, Wendela P. and Caan, Matthan W. A. and Malhotra, Anil K. and Szeszko, Philip R. and Duran, Marinus and Olabarriaga, Silvia D. and de Haan, Lieuwe},
    Date-Modified = {2016-07-19 08:12:39 +0000},
    Journal = {{Schizophrenia Bulletin}},
    Number = {4},
    Pages = {830-838},
    Title = {Polyunsaturated Fatty Acid Concentration Predicts Myelin Integrity in Early-Phase Psychosis},
    Volume = {39},
    Year = {2013}}
  • A. Rienstra, P. F. C. Groot, P. E. J. Spaan, C. B. L. M. Majoie, A. J. Nederveen, G. J. M. Walstra, J. F. M. de Jonghe, W. A. van Gool, S. D. Olabarriaga, V. V. Korkhov, and B. Schmand, “Symptom validity testing in memory clinics: hippocampal-memory associations and relevance for diagnosing mild cognitive impairment,” Journal of Clinical and Experimental Neuropsychology, vol. 35, iss. 1, pp. 59-70, 2013.
    [Bibtex]
    @article{rienstra:2013aa,
    Author = {Rienstra, Anne and Groot, Paul F. C. and Spaan, Pauline E. J. and Majoie, Charles B. L. M. and Nederveen, Aart J. and Walstra, Gerard J. M. and de Jonghe, Jos F. M. and van Gool, Willem A. and Olabarriaga, Silvia D. and Korkhov, Vladimir V. and Schmand, Ben},
    Date-Modified = {2016-07-19 08:13:09 +0000},
    Journal = {{Journal of Clinical and Experimental Neuropsychology}},
    Number = {1},
    Pages = {59-70},
    Title = {Symptom validity testing in memory clinics: Hippocampal-memory associations and relevance for diagnosing mild cognitive impairment},
    Volume = {35},
    Year = {2013}}
  • [DOI] M. Santcroos, B. D. C. van Schaik, S. Shahand, S. D. Olabarriaga, A. Luckow, and S. Jha, “Exploring dynamic enactment of scientific workflows using pilot-abstractions,” in Cluster, Cloud and Grid Computing (CCGrid), 2013 13th IEEE/ACM International Symposium on, 2013, pp. 311-318.
    [Bibtex]
    @inproceedings{santcroos:2013aa,
    Abstract = {Current workflow abstractions in general lack: (a) an adequate approach to handle distributed data and (b) proper separation between logical tasks and data-flow from their mapping onto physical locations. As the complexity and dynamism of data and processing distribution have increased, optimized mapping of logical tasks to physical resources have become a necessity to avoid bottlenecks. We argue that the management of dynamic data and compute should become part of the runtime system of workflow engines to enable workflows to scale as necessary to address big data challenges and fully exploit distributed computing infrastructures (DCI). In this paper we explore how the P* model for pilot-abstractions, which proposes a clear separation between the logical compute and data units and their realization as a job or a file in some physical resource, could provide these capabilities for such a runtime environment. The Pilot-API provides a general-purpose interface to pilot-abstractions and the ability to assign compute and data resources to them. We share our experience of using the case study of a DNA sequencing pipeline, to re-implement the workflow using the Pilot-API. This first exercise, which resulted in a running application that is discussed here, illustrates the potential of this API to address (a) and (b). Our initial results indicate that the pilot abstractions (as captured by the P* model)offer an interesting approach to explore the design of a new generation of workflow management systems and runtime environments that are capable of intelligently deciding on application-aware late binding to physical resources.},
    Author = {Santcroos, M. and van Schaik, B.D.C. and Shahand, S. and Olabarriaga, S.D. and Luckow, A. and Jha, S.},
    Booktitle = {{Cluster, Cloud and Grid Computing (CCGrid), 2013 13th IEEE/ACM International Symposium on}},
    Date-Modified = {2016-07-19 08:12:07 +0000},
    Doi = {10.1109/CCGrid.2013.17},
    Pages = {311-318},
    Title = {Exploring Dynamic Enactment of Scientific Workflows Using Pilot-Abstractions},
    Year = {2013},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/CCGrid.2013.17}}
  • [DOI] B. D. van Schaik, M. Santcroos, S. Madougou, A. Jongejan, A. H. van Kampen, and S. D. Olabarriaga, “E-bioscience solutions and challenges for next generation sequencing experiments,” in Proceedings of 2nd International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO) 2013, 2013, pp. 333-334.
    [Bibtex]
    @inproceedings{vanSchaik,
    Abstract = {Next generation sequencing (NGS) produces large volumes of data. To keep the
    processing time within bounds, there is the need to optimize the bioinformatics
    analysis pipelines. We have been using scientific workflow technology for agile
    development of analysis pipelines and grid infrastructure to accelerate the processing.
    Although these methods were successfully applied to a diverse range
    of sequencing experiments we also encountered several bottlenecks during the
    analysis. The challenge is to pinpoint the bottlenecks and to remove them to
    make optimal use of e-infrastructures for NGS experiments.
    The generic platform we have developed and work with, called e-BioInfra,
    is currently used for medical imaging, metabolomics and large scale DNA sequencing
    projects. It has been used for comparison of small genomes, analysis
    of RNAseq experiments[1, 2], virus discovery[3], and the analysis of exome sequencing
    experiments[4]. The platform has a layered architecture and is based on
    a national grid infrastructure. It consists of a workflow management system[5],
    several user interfaces for workflow submission[6], and a provenance store that
    gathers workflow execution information from the other system components[7].
    Upon execution the user can choose a previously developed workflow, define
    which files to analyze, and which parameters to use. The workflow management
    system then takes the input and translates these into jobs that are automatically
    executed on a distributed infrastructure.
    In an earlier study we showed that this approach can result in a 30x speedup
    compared to serial execution on a local system[8]. In practice we see that
    some applications perform well indeed and that similar speed-up rates can be
    obtained. However, with some software applications we experience high job error
    rates which are not all automatically recovered by the platform. One of the popular
    workflows we experienced problems with (BWA alignment) was optimized
    to reduce the error rate and decrease total workflow runtime[9]. A subsequent
    statistical analysis of the provenance store, which is originally meant to trace
    back all steps of an experiment, was used to identify main causes for failure[10].
    The improvements to the BWA workflow resulted in an increase of the success
    rate from 10% to 70% and a reduction of processing time to a third. The analysis
    of the provenance store indicated that BWA uses more memory than some sites
    offer, which was not obvious from manual inspection of the log files. This problem
    could be easily solved by blacklisting certain sites for BWA alignments.
    To summarize, the e-Bioscience platform hides the complexities of distributed
    computing infrastructures from end-users. It enables scientists to perform analysis
    faster and be flexible in tool integration in analysis workflows. It furthermore
    facilitates the sharing of data and methods via the e-infrastructure. By
    using the e-BioInfra platform, optimizing workflows, and thorough examination
    of provenance and logging information, the analysis of NGS data can be greatly
    accelerated.},
    Author = {van Schaik, Barbera DC and Santcroos, Mark and Madougou, Souley and Jongejan, Aldo and van Kampen, Antoine HC and Olabarriaga, S. D.},
    Booktitle = {{Proceedings of 2nd International Work-Conference on Bioinformatics and Biomedical Engineering (IWBBIO) 2013}},
    Date-Modified = {2016-07-19 08:11:55 +0000},
    Doi = {http://iwbbio.ugr.es/papers/iwbbio_061.pdf},
    Pages = {333-334},
    Title = {e-Bioscience Solutions and Challenges for Next Generation Sequencing Experiments},
    Year = {2013},
    Bdsk-Url-1 = {http://iwbbio.ugr.es/papers/iwbbio_061.pdf}}
  • S. Shahand, A. Benabdelkader, J. Huguet, M. Jaghouri, M. Santcroos, M. al Mourabit, P. F. C. Groot, M. W. A. Caan, A. H. C. van Kampen, and S. D. Olabarriaga, “A data-centric science gateway for computational neuroscience,” in Proceedings of the 5th International Workshop on Science Gateways, 2013.
    [Bibtex]
    @inproceedings{shahand:2013aa,
    Author = {Shahand, Shayan and Benabdelkader, Ammar and Huguet, Jordi and Jaghouri, Mahdi and Santcroos, Mark and al Mourabit, Mostapha and Groot, Paul F. C. and Caan, Matthan W. A. and van Kampen, Antoine H. C. and Olabarriaga, Silvia D.},
    Booktitle = {{Proceedings of the 5th International Workshop on Science Gateways}},
    Date-Modified = {2016-07-19 08:11:01 +0000},
    Month = {June},
    Title = {A Data-Centric Science Gateway for Computational Neuroscience},
    Year = {2013}}

2012

  • [DOI] M. W. A. Caan, S. Shahand, F. M. Vos, A. H. C. van Kampen, and S. D. Olabarriaga, “Evolution of grid-based services for diffusion tensor image analysis,” Future Generation Computer Systems, vol. 28, iss. 8, pp. 1194-1204, 2012.
    [Bibtex]
    @article{caan:2012aa,
    Abstract = {Analyzing Diffusion Tensor Image data of the human brain of large study groups is complex and demands new, sophisticated and computationally intensive pipelines that can efficiently be executed. We present our progress over the past five years in the development and porting of the DTI analysis pipeline to a grid infrastructure. Starting with simple jobs submitted from the command-line, we moved towards a workflow-based implementation and finally into the e-BioInfra Gateway, which offers a web interface for the execution of selected biomedical data analysis software on the Dutch Grid. This gateway is currently being actively used by neuroscientists and for educational purposes.},
    Author = {M.W.A. Caan and S. Shahand and F.M. Vos and A.H.C. van Kampen and S.D. Olabarriaga},
    Date-Modified = {2016-07-19 08:13:48 +0000},
    Doi = {10.1016/j.future.2012.03.007},
    Journal = {{Future Generation Computer Systems}},
    Number = {8},
    Pages = {1194 - 1204},
    Title = {Evolution of grid-based services for Diffusion Tensor Image analysis},
    Volume = {28},
    Year = {2012},
    Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.future.2012.03.007}}
  • S. Madougou, M. Santcroos, A. Benabdelkader, B. D. van Schaik, S. Shahand, V. Korkhov, A. H. van Kampen, and S. D. Olabarriaga, “Provenance for distributed biomedical workflow execution,” in Studies in Health Technology and Informatics, 2012, pp. 91-100.
    [Bibtex]
    @inproceedings{madougou:2012aa,
    Author = {Madougou, S. and Santcroos, M. and Benabdelkader, A. and van Schaik, B. D. and Shahand, S. and Korkhov, V. and van Kampen, A. H. and Olabarriaga, S. D.},
    Booktitle = {{Studies in Health Technology and Informatics}},
    Date-Modified = {2016-07-19 08:15:43 +0000},
    Pages = {91--100},
    Publisher = {{IOS Press}},
    Title = {{{P}rovenance for distributed biomedical workflow execution}},
    Volume = {175},
    Year = {2012}}
  • [DOI] H. Marquering, J. Engelbers, P. Groot, C. Majoie, L. Beenen, A. van Kampen, and S. D. Olabarriaga, “Optimization and parallelization of the matched masked bone elimination method for cta.,” in Proceedings of the MICCAI workshop on Data- and Compute-Intensive Clinical and Translational Imaging Applications, 2012.
    [Bibtex]
    @inproceedings{Marquering,
    Author = {Marquering, Henk and Engelbers, Jeroen and Groot, Paul and Majoie, Charles and Beenen, Ludo and van Kampen, Antoine and Olabarriaga, S. D.},
    Booktitle = {{Proceedings of the MICCAI workshop on Data- and Compute-Intensive Clinical and Translational Imaging Applications}},
    Date-Modified = {2016-07-19 08:15:11 +0000},
    Doi = {http://proton.polytech.unice.fr/DCICTIA-MICCAI12/dcictia12-proceedings.pdf},
    Title = {Optimization and Parallelization of the Matched Masked Bone Elimination Method for CTA.},
    Year = {2012},
    Bdsk-Url-1 = {http://proton.polytech.unice.fr/DCICTIA-MICCAI12/dcictia12-proceedings.pdf}}
  • E. Mouw, G. van’t Noordende, A. H. van Kampen, B. Louter, M. Santcroos, and S. D. Olabarriaga, “Legal constraints on genetic data processing in European grids,” in Proceedings of HealthGrid 2012, 2012, pp. 49-58.
    [Bibtex]
    @inproceedings{mouw:2012aa,
    Author = {Mouw, Evert and van't Noordende, G. and van Kampen, A. H. and Louter, B. and Santcroos, M. and Olabarriaga, S. D.},
    Booktitle = {{Proceedings of HealthGrid 2012}},
    Date-Modified = {2016-07-19 08:14:41 +0000},
    Pages = {49--58},
    Publisher = {{IOS Press}},
    Title = {{{L}egal constraints on genetic data processing in {E}uropean grids}},
    Volume = {175},
    Year = {2012}}
  • [DOI] S. Shahand, M. Santcroos, A. H. C. Kampen, and S. Olabarriaga, “A grid-enabled gateway for biomedical data analysis,” Journal of Grid Computing, vol. 10, iss. 4, pp. 725-742, 2012.
    [Bibtex]
    @article{shahand:2012ab,
    Abstract = {Biomedical researchers can leverage Grid computing technology to address their increasing demands for data- and compute-intensive data analysis. However, usage of existing Grid infrastructures remains difficult for them. The e-infrastructure for biomedical science (e-BioInfra) is a platform with services that shield middleware complexities, in particular workflow management and monitoring. These services can be invoked from a web-based interface, called e-BioInfra Gateway, to perform large scale data analysis experiments, such that the biomedical researchers can focus on their own research problems. The gateway was designed to simplify usage both by biomedical researchers and e-BioInfra administrators, and to support straightforward extensions with new data analysis methods. In this paper we present the architecture and implementation of the gateway, also showing statistics for its usage. We also share lessons learned during the gateway development and operation. The gateway is currently used in several biomedical research projects and in teaching medical students the principles of data analysis.},
    Author = {Shahand, Shayan and Santcroos, Mark and Kampen, Antoine H.C. and Olabarriaga, S{\'\i}lvia},
    Date-Modified = {2016-07-19 08:13:41 +0000},
    Doi = {10.1007/s10723-012-9233-4},
    Journal = {{Journal of Grid Computing}},
    Number = {4},
    Pages = {725-742},
    Title = {A Grid-Enabled Gateway for Biomedical Data Analysis},
    Volume = {10},
    Year = {2012},
    Bdsk-Url-1 = {http://dx.doi.org/10.1007/s10723-012-9233-4}}
  • [DOI] S. Shahand, M. W. Caan, A. H. van Kampen, and S. D. Olabarriaga, “Integrated support for neuroscience research: from study design to publication,” in Studies in Health Technology and Informatics, 2012, pp. 195-204.
    [Bibtex]
    @inproceedings{shahand:2012aa,
    Abstract = {Computational neuroscience is a new field of research in which neurodegenerative diseases are studied with the aid of new imaging techniques and computation facilities. Researchers with different expertise collaborate in these studies. A study requires scalable computational and storage capacity and information management facilities to succeed. Many virtual laboratories are proposed and developed to facilitate these studies, however most of them cover only the parts related to the computational data processing. In this paper we describe and analyse the phases of the computational neuroscience studies including the actors, the tasks they perform, and the characteristics of each phase. Based on these we identify the required properties and functionalities of a virtual laboratory that supports the actors and their tasks throughout the complete study.},
    Author = {Shahand, S. and Caan, M. W. and van Kampen, A. H. and Olabarriaga, S. D.},
    Booktitle = {{Studies in Health Technology and Informatics}},
    Date-Modified = {2016-07-19 08:14:56 +0000},
    Doi = {10.3233/978-1-61499-054-3-195},
    Pages = {195--204},
    Publisher = {{IOS Press}},
    Title = {{{I}ntegrated support for neuroscience research: from study design to publication}},
    Volume = {175},
    Year = {2012},
    Bdsk-Url-1 = {http://dx.doi.org/10.3233/978-1-61499-054-3-195}}
  • M. de Vries, B. B. Oude Munnink, M. Deijs, M. Canuti, S. M. Koekkoek, R. Molenkamp, M. Bakker, S. Jurriaans, B. D. C. van Schaik, A. C. Luyf, S. D. Olabarriaga, A. H. C. van Kampen, and L. van der Hoek, “Performance of VIDISCA-454 in feces-suspensions and serum,” Viruses, vol. 4, iss. 8, pp. 1328-1334, 2012.
    [Bibtex]
    @article{vries:2012aa,
    Author = {de Vries, Michel and Oude Munnink, Bas B. and Deijs, Martin and Canuti, Marta and Koekkoek, Sylvie M. and Molenkamp, Richard and Bakker, Margreet and Jurriaans, Suzanne and van Schaik, Barbera D. C. and Luyf, Angela C. and Olabarriaga, Silvia D. and van Kampen, Antoine H. C. and van der Hoek, Lia},
    Date-Modified = {2016-07-19 08:15:24 +0000},
    Journal = {Viruses},
    Number = {8},
    Pages = {1328--1334},
    Title = {Performance of {VIDISCA-454} in Feces-Suspensions and Serum},
    Volume = {4},
    Year = {2012}}
  • G. A. van Wingen, E. Geuze, M. W. A. Caan, T. Kozicz, S. D. Olabarriaga, D. Denys, E. Vermetten, and G. Fernández, “Persistent and reversible consequences of combat stress on the mesofrontal circuit and cognition,” Proceedings of the National Academy of Sciences, vol. 109, iss. 38, pp. 15508-15513, 2012.
    [Bibtex]
    @article{wingen:2012aa,
    Author = {van Wingen, Guido A. and Geuze, Elbert and Caan, Matthan W. A. and Kozicz, Tam{\'a}s and Olabarriaga, Silvia D. and Denys, Damiaan and Vermetten, Eric and Fern{\'a}ndez, Guill{\'e}n},
    Date-Modified = {2016-07-19 08:15:32 +0000},
    Journal = {{Proceedings of the National Academy of Sciences}},
    Number = {38},
    Pages = {15508-15513},
    Title = {Persistent and reversible consequences of combat stress on the mesofrontal circuit and cognition},
    Volume = {109},
    Year = {2012}}

2011

  • [DOI] V. Korkhov, D. Krefting, T. Kukla, G. Z. Terstyanszky, M. Caan, and S. D. Olabarriaga, “Exploring workflow interoperability tools for neuroimaging data analysis,” in Proceedings of the 6th Workshop on Workflows in Support of Large-scale Science, New York, NY, USA, 2011, pp. 87-96.
    [Bibtex]
    @inproceedings{Korkhov:2011:EWI:2110497.2110508,
    Abstract = {Neuroimaging is a field that benefits from distributed computing infrastructures (DCIs) to perform data processing and analysis, which is often achieved using grid workflow systems. Collaborative research in neuroimaging requires ways to facilitate exchange between different groups, in particular to enable sharing, re-use and interoperability of applications implemented as workflows. The SHIWA project provides solutions to facilitate sharing and exchange of workflows between workflow systems and DCI resources. In this paper we present and analyse how the SHIWA platform was used to implement various usage scenarios in which workflow exchange supports collaboration in neuroscience. The SHIWA platform and the implemented solutions are described and analysed from the "user" perspective, in this case the workflow developers and the neuroscientists. We conclude that the platform in its current form is valuable for the foreseen usage scenarios, and we identify remaining challenges concerning management of multiple credentials and data transfers across DCIs.},
    Address = {New York, NY, USA},
    Author = {Korkhov, Vladimir and Krefting, Dagmar and Kukla, Tamas and Terstyanszky, Gabor Z. and Caan, Matthan and Olabarriaga, Silvia D.},
    Booktitle = {{Proceedings of the 6th Workshop on Workflows in Support of Large-scale Science}},
    Date-Modified = {2016-07-19 08:16:45 +0000},
    Doi = {10.1145/2110497.2110508},
    Pages = {87--96},
    Publisher = {ACM},
    Series = {WORKS '11},
    Title = {Exploring Workflow Interoperability Tools for Neuroimaging Data Analysis},
    Year = {2011},
    Bdsk-Url-1 = {http://dx.doi.org/10.1145/2110497.2110508}}
  • D. Krefting, T. Glatard, V. Korkhov, J. Montagnat, and S. D. Olabarriaga, “Enabling grid interoperability at workflow level.,” in Proceedings of the Grid WorkflowWorkshop 2011 (GWW 2011), 2011.
    [Bibtex]
    @inproceedings{Krefting,
    Abstract = {In the last years various distributed computing
    infrastructures (DCIs) have been developed to support national and
    international research activities. Today several applications from
    diverse domains have been ported to them. For example, workflowbased
    grid applications for medical imaging have been developed
    in the Netherlands within the VL-e project, in France within the
    EGI biomed VO and in Germany within the German medical D-Grid
    projects. These applications are based on the resources and workflow
    systems provided by respective grid infrastructures, and researchers
    now face difficulties to exchange applications and data across
    the DCIs. This would be important to obtain access to additional
    resources and to enable sharing of applications and methodology.
    Unfortunately today the mobility across DCIs at application level is
    hardly supported.
    Results: The European project SHIWA - Sharing Interoperable
    Workflows for large-scale scientific simulations on Available DCIs1
    aims to realize interoperability at workflow level. This will allow domain
    researchers to share and reuse their scientific workflows across DCIs.
    Different use cases are identified which result in a two-fold approach:
    coarse-grained and fine-grained workflow interoperability. First results
    are presented for two pilot applications - neuroimaging and chemistry
    - and two workflow systems - MOTEUR and GWES. We analyze
    the similarities and differences between these systems, and show
    implementation strategies for easily combine and translate scientific
    workflows. These results enable sharing and reusing workflows and
    grid services between EGI, D-Grid, and Dutch Grid infrastructures
    Availability: The workflow managers GWES and MOTEUR are both
    open source and free for academic use. The mentioned workflows will
    be published within the SHIWA platform.},
    Author = {Krefting, D. and Glatard, T. and Korkhov, V. and Montagnat, J. and Olabarriaga, S. D.},
    Booktitle = {{Proceedings of the Grid WorkflowWorkshop 2011 (GWW 2011)}},
    Date-Modified = {2016-07-19 08:16:23 +0000},
    Month = {March},
    Title = {Enabling Grid Interoperability at Workflow Level.},
    Year = {2011}}
  • [DOI] Y. Mohammed, S. Shahand, V. Korkhov, A. C. M. Luyf, B. D. C. van Schaik, M. W. A. Caan, A. H. C. van Kampen, M. Palmblad, and S. D. Olabarriaga, “Data decomposition in biomedical e-science applications,” in e-Science Workshops (eScienceW), 2011 IEEE Seventh International Conference on, 2011, pp. 158-165.
    [Bibtex]
    @inproceedings{mohammed:2011ab,
    Abstract = {As the focus of e-Science is moving toward the forth paradigm and data intensive science, data access remains dependent on the architecture of the used e-Science infrastructure. Such architecture is in general job-driven, i.e., a (grid) job is a sequence of commands that run on the same worker node. Making use of the infrastructure involves having a parallelized application. This is done foremost by data decomposition. In general practice of parallel programming, data decomposition depends on the programmer's experience and knowledge about the used data and the algorithm/application. On the other hand, data mining scientists have an established foundation for data decomposition, automatic decomposition methods are already in use, methodologies and patterns are defined. Our experience in porting biomedical applications to the Dutch e-Science infrastructure shows that the used data decomposition to gain parallelism fit to some degree a subgroup of the data mining decomposition patterns, i.e., object set decomposition. In this paper we discuss porting three biomedical packages to a grid computing environment, two for medical imaging and one for DNA sequencing. We show how the data access of the applications was reengineered around the executables to make use of the parallel capacity of e-Science infrastructure.},
    Author = {Mohammed, Y. and Shahand, S. and Korkhov, V. and Luyf, A.C.M. and van Schaik, B.D.C. and Caan, M.W.A. and van Kampen, A.H.C. and Palmblad, M. and Olabarriaga, S.D.},
    Booktitle = {{e-Science Workshops (eScienceW), 2011 IEEE Seventh International Conference on}},
    Date-Modified = {2016-07-19 08:16:16 +0000},
    Doi = {10.1109/eScienceW.2011.7},
    Month = {dec.},
    Pages = {158 -165},
    Title = {Data Decomposition in Biomedical e-Science Applications},
    Year = {2011},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/eScienceW.2011.7}}
  • S. Shahand, M. Santcroos, Y. Mohammed, V. Korkhov, A. Luyf, A. van Kampen, and S. Olabarriaga, “Front-ends to Biomedical Data Analysis on Grids,” in Proceedings of HealthGrid 2011, Bristol, UK, 2011.
    [Bibtex]
    @inproceedings{shahand:2011aa,
    Address = {Bristol, UK},
    Author = {Shahand, S. and Santcroos, M. and Mohammed, Y. and Korkhov, V. and Luyf, A. and van Kampen, A. and Olabarriaga, S.},
    Booktitle = {{Proceedings of HealthGrid 2011}},
    Date-Modified = {2016-07-19 08:16:53 +0000},
    Title = {{Front-ends to Biomedical Data Analysis on Grids}},
    Year = {2011}}

2010

  • [DOI] M. Caan, H. Khedoe, D. Poot, A. den Dekker, S. Olabarriaga, K. Grimbergen, L. van Vliet, and F. Vos, “Estimation of diffusion properties in crossing fiber bundles,” IEEE Transactions on Medical Imaging, vol. 29, iss. 8, pp. 1504-15, 2010.
    [Bibtex]
    @article{Caan,
    Abstract = {There is an ongoing debate on how to model diffusivity in fiber crossings. We propose an optimization framework for the selection of a dual tensor model and the set of diffusion weighting parameters b, such that both the diffusion shape and orientation parameters can be precisely as well as accurately estimated. For that, we have adopted the Cram{\'e}r-Rao lower bound (CRLB) on the variance of the model parameters, and performed Monte Carlo simulations. We have found that the axial diffusion lambda(parallel) needs to be constrained, while an isotropic fraction can be modeled by a single parameter f(iso). Under these circumstances, the Fractional Anisotropy (FA) of both tensors can theoretically be independently estimated with a precision of 9% (at SNR = 25). Levenberg-Marquardt optimization of the Maximum Likelihood function with a Rician noise model approached this precision while the bias was insignificant. A two-element b-vector b = [1.0 3.5] x 10(3) mm(-2)s was found to be sufficient for estimating parameters of heterogeneous tissue with low error. This has allowed us to estimate consistent FA-profiles along crossing tracts. This work defines fundamental limits for comparative studies to correctly analyze crossing white matter structures.},
    Author = {Caan, MW and Khedoe, HG and Poot, DH and den Dekker, AJ and Olabarriaga, SD and Grimbergen, KA and van Vliet, LJ and Vos, FM},
    Date-Modified = {2016-07-19 08:17:50 +0000},
    Doi = {10.1109/TMI.2010.2049577},
    Journal = {{IEEE Transactions on Medical Imaging}},
    Number = {8},
    Pages = {1504-15},
    Title = {Estimation of diffusion properties in crossing fiber bundles},
    Volume = {29},
    Year = {2010},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/TMI.2010.2049577}}
  • [DOI] F. Gwadry-Sridhar, S. D. Olabarriaga, A. van Kampen, M. Bauer, and T. Solomonides, “Hitting the ground running: Healthgrid deployment and adoption,” in Proceedings of HealthGrid 2010, 2010, pp. 40-51.
    [Bibtex]
    @inproceedings{Gwadry-Sridhar,
    Abstract = {We consider the issues of healthgrid development, deployment and adoption in health care and research environments. While healthgrid technology could be deployed to support advanced medical research, we are not seeing its wide adoption. Understanding why this technology is not being exploited is one purpose of this paper. We do so in light of the seminal Healthgrid White Paper and the SHARE roadmap. We also address barriers to adoption and successes by presenting experiences in North America and Europe. By critically appraising where we are, we hope that we can hit the ground running in the near future.},
    Author = {Gwadry-Sridhar, F. and Olabarriaga, S.D. and van Kampen, A. and Bauer, M. and Solomonides, T.},
    Booktitle = {{Proceedings of HealthGrid 2010}},
    Date-Modified = {2016-07-19 08:18:08 +0000},
    Doi = {http://www.ncbi.nlm.nih.gov/pubmed/20543425},
    Pages = {40-51},
    Publisher = {IOS Press},
    Series = {{Studies in Health Technology and Informatics}},
    Title = {{Hitting the ground running: Healthgrid deployment and adoption}},
    Year = {2010},
    Bdsk-Url-1 = {http://www.ncbi.nlm.nih.gov/pubmed/20543425}}
  • [DOI] A. Luyf, B. van Schaik, M. de Vries, F. Baas, A. van Kampen, and S. Olabarriaga, “Initial steps towards a production platform for DNA sequence analysis on the grid,” BMC Bioinformatics, vol. 11, iss. 1, p. 598, 2010.
    [Bibtex]
    @article{21156038,
    Abstract = {BACKGROUND:Bioinformatics is confronted with a new data explosion due to the availability of high throughput DNA sequencers. Data storage and analysis becomes a problem on local servers, and therefore it is needed to switch to other IT infrastructures. Grid and workflow technology can help to handle the data more efficiently, as well as facilitate collaborations. However, interfaces to grids are often unfriendly to novice users.RESULTS:In this study we reused a platform that was developed in the VL-e project for the analysis of medical images. Data transfer, workflow execution and job monitoring are operated from one graphical interface. We developed workflows for two sequence alignment tools (BLAST and BLAT) as a proof of concept. The analysis time was significantly reduced. All workflows and executables are available for the members of the Dutch Life Science Grid and the VL-e Medical virtual organizations All components are open source and can be transported to other grid infrastructures.CONCLUSIONS:The availability of in-house expertise and tools facilitates the usage of grid resources by new users. Our first results indicate that this is a practical, powerful and scalable solution to address the capacity and collaboration issues raised by the deployment of next generation sequencers. We currently adopt this methodology on a daily basis for DNA sequencing and other applications. More information and source code is available via http://www.bioinformaticslaboratory.nl/ webcite},
    Author = {Luyf, Angela and van Schaik, Barbera and de Vries, Michel and Baas, Frank and van Kampen, Antoine and Olabarriaga, Silvia},
    Date-Modified = {2016-07-19 08:18:22 +0000},
    Doi = {10.1186/1471-2105-11-598},
    Journal = {{BMC Bioinformatics}},
    Number = {1},
    Pages = {598},
    Title = {Initial steps towards a production platform for {DNA} sequence analysis on the grid},
    Volume = {11},
    Year = {2010},
    Bdsk-Url-1 = {http://dx.doi.org/10.1186/1471-2105-11-598}}
  • [DOI] S. D. Olabarriaga and J. Montagnat, “Special Section: Medical Imaging on Grids,” Future Generation Computer Systems, vol. 26, iss. 4, pp. 678-680, 2010.
    [Bibtex]
    @article{Olabarriaga:2010:SSM:1715948.1716284,
    Author = {Olabarriaga, S. D. and Montagnat, Johan},
    Date-Modified = {2016-07-19 08:17:33 +0000},
    Doi = {10.1016/j.future.2009.08.015},
    Journal = {{Future Generation Computer Systems}},
    Month = apr,
    Number = {4},
    Pages = {678--680},
    Title = {{Special Section: Medical Imaging on Grids}},
    Volume = {26},
    Year = {2010},
    Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.future.2009.08.015}}
  • [DOI] S. D. Olabarriaga, T. Glatard, and P. T. de Boer, “A virtual laboratory for medical image analysis,” IEEE Trans. Info. Tech. Biomed., vol. 14, iss. 4, pp. 979-985, 2010.
    [Bibtex]
    @article{Olabarriaga:2010:VLM:1856563.1856574,
    Abstract = {This paper presents the design, implementation, and usage of a virtual laboratory for medical image analysis. It is fully based on the Dutch grid, which is part of the Enabling Grids for E-sciencE (EGEE) production infrastructure and driven by the gLite middleware. The adopted service-oriented architecture enables decoupling the user-friendly clients running on the user's workstation from the complexity of the grid applications and infrastructure. Data are stored on grid resources and can be browsed/viewed interactively by the user with the Virtual Resource Browser (VBrowser). Data analysis pipelines are described as Scufl workflows and enacted on the grid infrastructure transparently using the MOTEUR workflow management system. VBrowser plug-ins allow for easy experiment monitoring and error detection. Because of the strict compliance to the grid authentication model, all operations are performed on behalf of the user, ensuring basic security and facilitating collaboration across organizations. The system has been operational and in daily use for eight months (December 2008), with six users, leading to the submission of 9000 jobs/month in average and the production of several terabytes of data.},
    Author = {Olabarriaga, S. D. and Glatard, Tristan and de Boer, Piter T.},
    Date-Modified = {2016-07-19 08:17:14 +0000},
    Doi = {10.1109/TITB.2010.2046742},
    Journal = {{IEEE Trans. Info. Tech. Biomed.}},
    Month = jul,
    Number = {4},
    Pages = {979--985},
    Title = {A Virtual Laboratory for Medical Image Analysis},
    Volume = {14},
    Year = {2010},
    Bdsk-Url-1 = {http://dx.doi.org/10.1109/TITB.2010.2046742}}

2008

  • T. Glatard, K. Boulebiar, and S. D. Olabarriaga, “Workflow integration in VL-e medical,” in 21st International Symposium on Computer-Based Medical Systems (CBMS), 2008, pp. 144-146.
    [Bibtex]
    @inproceedings{glatard:2008jo,
    Author = {Glatard, Tristan and Boulebiar, Kamel and Olabarriaga, Silvia D},
    Booktitle = {{21st International Symposium on Computer-Based Medical Systems (CBMS)}},
    Date-Modified = {2016-07-19 08:18:45 +0000},
    Pages = {144--146},
    Publisher = {IEEE},
    Title = {{Workflow integration in VL-e medical}},
    Year = {2008}}

2006

  • S. D. Olabarriaga, P. T. De boer, K. Maheshwari, A. Belloum, J. G. Snel, A. J. Nederveen, and M. Bouwhuis, “Virtual Lab for fMRI: Bridging the Usability Gap,” in 2nd IEEE International Conference on e-Science and Grid Computing, 2006, p. 53.
    [Bibtex]
    @inproceedings{olabarriaga:2006et,
    Author = {Olabarriaga, S.D. and De boer, P.T. and Maheshwari, Ketan and Belloum, A and Snel, J.G. and Nederveen, A.J. and Bouwhuis, M.},
    Booktitle = {{2nd IEEE International Conference on e-Science and Grid Computing}},
    Date-Modified = {2016-07-19 08:18:54 +0000},
    Month = dec,
    Pages = {53},
    Title = {{Virtual Lab for fMRI: Bridging the Usability Gap}},
    Year = {2006}}