e-BioGrid_NBIC Conference 2011 april 20

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e-BioGrid support in developing e-science infrastructure for life science research.

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e-BioGrid_NBIC Conference 2011 april 20

  1. 1. e-BioGrid <ul><li>Enabling Life Science Research and Development </li></ul><ul><li>Irene Nooren </li></ul><ul><li>NBIC Conference 2011 </li></ul>
  2. 2. The consequences of the life science omics revolution Huge & many data sets Increased complexity Overload = + It has to be on one of these tapes
  3. 3. Dutch Computing Infrastructure <ul><li>High-performance computing and storage resources, </li></ul><ul><ul><ul><li>The Life Science Grid </li></ul></ul></ul><ul><ul><ul><li>National supercomputer </li></ul></ul></ul><ul><ul><ul><li>National compute cluster, GPU’s </li></ul></ul></ul><ul><ul><ul><li>Self service High performance compute Cloud </li></ul></ul></ul><ul><ul><ul><li>Hadoop </li></ul></ul></ul><ul><ul><ul><li>Petabytes of disk and tape storage. </li></ul></ul></ul><ul><li>Tailored support, training and advice </li></ul>
  4. 4. e-BioGrid: e-science approach <ul><li>Bridge between BiG Grid and life science community </li></ul><ul><li>Create e-science infrastructure and methods </li></ul><ul><ul><li>Inventory of needs and requirements of end-users </li></ul></ul><ul><ul><li>Bring together expertise and disciplines </li></ul></ul><ul><ul><li>Design and develop e-science based Problem-Solving Environments </li></ul></ul><ul><ul><li>Connect commonly used software tools to BiG Grid facilities </li></ul></ul><ul><ul><li>Make infrastructure available to life-science researchers </li></ul></ul><ul><li>Funded by BiG Grid, led by partners NBIC, Nikhef and NCF (NWO) </li></ul>e-Science Computationally intensive science in networked environment Problem-Solving Environments Software components solving ICT obstacles
  5. 5. <ul><li>Selected e-bioscience application areas </li></ul><ul><li>NGS: Next-generation sequencing </li></ul><ul><li>MAT: Microarray technology </li></ul><ul><li>MAS: Mass spectrometry </li></ul><ul><li>NSC: Nanoscopy & imaging </li></ul><ul><li>BBC: Biobanking/Cohort Studies </li></ul><ul><li>NMR: NMR Spectroscopy & modelling </li></ul>UvA Timo Breit Irene Nooren Han Rauwerda LU Joost Kok Erwin Bakker SARA Maurice Bouwhuis Machiel Jansen e-BioGrid organization The life science part of BiG Grid
  6. 6. Alignment with NBIC BioAssist e-BioScience Life Science Research Research Support BioAssist Engineering Team Genomics Bio-interpret. Biobanking Proteomics … Short cooperative projects Task force Tools TA project PSEs NGS MAS MAT NCS BBC BiG Grid BioAssist Support & Development Team Operations Team Cooperative projects Analysis, design & implementation of software environment Infrastructure Installation and running of the compute and storage systems e-Core e-BioGrid Bioinformatics tools oriented ICT Infrastructure oriented
  7. 7. Projects <ul><li>Main projects </li></ul><ul><ul><li>2-3 years in each of the technology areas </li></ul></ul><ul><ul><li>1.0 FTE implementer, 0.5 FTE BiG Grid technical support </li></ul></ul><ul><ul><li>All 6 have been assigned </li></ul></ul><ul><li>Dedicated projects </li></ul><ul><ul><li>Max. 3 months </li></ul></ul><ul><ul><li>Projects may be proposed </li></ul></ul>
  8. 8. e-BioGrid: status <ul><li>Start e-BioGrid: 1 September 2010 </li></ul><ul><li>5 main projects ongoing: MAT, NSC, NGS, BBC, NMR </li></ul><ul><li>10 dedicated projects ongoing in several technology areas and generic infrastructure </li></ul><ul><li>Ongoing life science computing making use of BiG Grid facilities </li></ul>Get involved Anyone with relevant project ideas is invited to contact us: [email_address]
  9. 9. www.e-biogrid.nl
  10. 10. Example: MAT main project <ul><li>Goal : Create infrastructure to design probes for multistrain prokaryotic samples in tiling array. </li></ul><ul><li>Solution : Microarray platform application using bioinformatics alignment tools </li></ul><ul><li>Result : Webbased ArrayDesigner </li></ul>See Application Showcase Linda Bakker
  11. 11. Example: NGS dedicated project <ul><li>Goal : GWA study analysis is computationally intensive. Use computing hardware and technology more efficiently either by making use of GPUs or by optimizing the algorithms used. </li></ul><ul><li>Solution : adapting the computing algorithm by using symbolic algebra </li></ul><ul><li>Result : 20-40 times gain in computing time </li></ul>
  12. 12. Main objectives e-BioGrid <ul><li>Create a national support basis for e-BioScience to both expert bioinformaticians and expert life scientists. </li></ul><ul><li>Exploit BIG Grid infrastructure in the life science R&D. </li></ul><ul><li>Create functional Problem Solving Environments (PSEs), e-infrastructure for the selected technology areas that deal with high demand in computing or data resources </li></ul><ul><li>Connect with the NBIC-BioAssist and BiG Grid programs. </li></ul>
  13. 13. e-BioGrid <ul><li>Infrastructure support from the e-BioGrid team is available for life science research </li></ul><ul><li>For project proposals contact </li></ul><ul><li>Irene Nooren </li></ul><ul><li>Project manager e-BioGrid </li></ul><ul><li>[email_address] </li></ul>Also at this conference Poster 53. Irene Nooren Application Showcase. Linda Bakker Workshop. Evert Lammerts www.e-biogrid.nl

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