CSHL Biological Data Science conference (9-12 Nov 2022)

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Cata Vallejos

Sep 9, 2022, 10:25:53 AM9/9/22
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Dear all,

The fifth meeting on Biological Data Science comes back to Cold Spring Harbor Laboratory this year (9-12 Nov 2022).  

The scope of this 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.

Abstract Deadline (consideration for a talk): September 16, 2022

Abstracts for poster presentations will be accepted until October 1, 2022

Discussion Themes:
  • Single Cell
  • Personalized Medicine and Biomarkers
  • Imaging
  • Machine Learning
  • Algorithmics
  • Tools, Infrastructure, and Visualization
Keynote Speakers:
Adam Phillippy, National Human Genome Research Institute
Molly Przeworski, Columbia University

Confirmed Discussion Leaders: 
Rosa Alcazar, Clovis Community College
Spiros Denaxas, University College London
Jeremy Goecks
, Oregon Health and Science University
Elinor Karlsson, University of Massachusetts Medical School
Stephanie Hicks, Johns Hopkins University
Johannes Köster, University of Duisberg-Essen, Germany
Michael Love, 
University of North Carolina
Tychele Turner, 
Washington University Schoolof Medicine

Robert Patro, University of Maryland
David Kelley, Calico Labs
Sanja Vickovic, New York Genome Center
Marinka Zitnik, Harvard University

More information about the meeting is available here

We look forward to seeing you at Cold Spring Harbor Laboratory in November.

Best wishes,

Catalina (on behalf of the organisers)


Barbara Engelhardt, Princeton University
Michael Schatz, Johns Hopkins University
Catalina Vallejos Meneses, University of Edinburgh, UK

Catalina Vallejos M.

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