Biological Data Science

Country: USA

City: Cold Spring Harbor

Abstr. due: 22.08.2014

Dates: 05.11.14 — 08.11.14

Area Of Sciences: Biology;

Organizing comittee e-mail:

Organizers: Broad Institute of Harvard and MIT, Cold Spring Harbor Laboratory, Amazon Web Services


We are pleased to announce a new meeting on Biological Data Science, which will begin on Wednesday, November 5th at 7:30 p.m. and conclude with lunch on Saturday, November 8th. The scope of this new CSHL meeting will be the infrastructure, software, and algorithms needed to analyze large data sets in biological research. We welcome abstracts from researchers in both academia and industry who work on technical aspects of the discussion topics in all areas of biology, from genomics to imaging. We also welcome abstracts from translational and clinical researchers who regularly mine large data sets as part of their projects. The goal is to assemble a multidisciplinary audience that will discuss best practices, identify challenges, and highlight successes in the analysis of large biological data sets.

Discussion topics:

    • Data Infrastructure: storage, access, databases, and data standards
    • Compute Infrastructure: processors, clouds, and workflows
    • Scalable Algorithmics: searching, streaming, and randomized or parallel algorithms
    • Mining Biological Data: machine learning, statistics, normalization, modeling, inference, and visualization
    • Software for Biologists: creating, disseminating, training, and funding such software
    • Knowledge Extraction: application areas and data integration
    • Sociology: legal, privacy, and ethical issues, as well as technologies for human data

Discussion leaders:

  • Mark Gerstein, Yale University
  • Ben Langmead, Johns Hopkins University
  • Kristin Lauter, Microsoft Research
  • Ronald Margolis, National Institutes of Health Big Data to Knowledge (NIH BD2K)
  • Matt Massie, University of California Berkeley AMPLab
  • James Taylor, Johns Hopkins University
  • Kaitlin Thaney, Mozilla Science Lab
  • Olga Troyanskaya, Princeton University
  • Rick Stevens, Argonne National Laboratory and the University of Chicago
Abstracts are welcome for consideration as poster and platform presentations and should contain new and unpublished material. Status of abstracts (talk versus poster) will be posted on our Web site as soon as decisions have been made by the organizers.

Conference Web-Site: