Difference between revisions of "PSB 2021"

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|Start date=2021/01/03
 
|Start date=2021/01/03
 
|End date=2021/01/07
 
|End date=2021/01/07
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|Submission deadline=2020/08/03
 
|Homepage=http://psb.stanford.edu/
 
|Homepage=http://psb.stanford.edu/
 
|Twitter account=@PacSymBiocomp
 
|Twitter account=@PacSymBiocomp
|City=Hawaii
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|City=Big Island of Hawaii
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|State=Hawaii
 
|Country=USA
 
|Country=USA
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|Abstract deadline=2020/11/15
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|Paper deadline=2020/08/03
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|Workshop deadline=2020/02/10
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|Notification=2020/09/14
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|Camera ready=2020/10/01
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|Submitting link=http://psb.wufoo.com/forms/psb-paper-submission/
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|has general chair=Tiffany Murray
 
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The twenty-six Pacific Symposium on Biocomputing (PSB), will be held January 3-7, 2021 at the Fairmont Orchid on the Big Island of Hawaii. PSB will bring together top researchers from North America, the Asian Pacific nations, Europe and around the world to exchange research results and address open issues in all aspects of computational biology. PSB will provide a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. PSB intends to attract a balanced combination of computer scientists and biologists, presenting significant original research, demonstrating computer systems, and facilitating formal and informal discussions on topics of importance to computational biology.
 
The twenty-six Pacific Symposium on Biocomputing (PSB), will be held January 3-7, 2021 at the Fairmont Orchid on the Big Island of Hawaii. PSB will bring together top researchers from North America, the Asian Pacific nations, Europe and around the world to exchange research results and address open issues in all aspects of computational biology. PSB will provide a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. PSB intends to attract a balanced combination of computer scientists and biologists, presenting significant original research, demonstrating computer systems, and facilitating formal and informal discussions on topics of importance to computational biology.

Latest revision as of 14:32, 30 April 2020

PSB 2021
26th Pacific Symposium on Biocomputing
Event in series PSB
Dates 2021/01/03 (iCal) - 2021/01/07
Homepage: http://psb.stanford.edu/
Twitter account: @PacSymBiocomp
Submitting link: http://psb.wufoo.com/forms/psb-paper-submission/
Location
Location: Big Island of Hawaii, Hawaii, USA
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Important dates
Workshops: 2020/02/10
Abstracts: 2020/11/15
Papers: 2020/08/03
Submissions: 2020/08/03
Notification: 2020/09/14
Camera ready due: 2020/10/01
Committees
General chairs: Tiffany Murray
Table of Contents
Tweets by @PacSymBiocomp


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The twenty-six Pacific Symposium on Biocomputing (PSB), will be held January 3-7, 2021 at the Fairmont Orchid on the Big Island of Hawaii. PSB will bring together top researchers from North America, the Asian Pacific nations, Europe and around the world to exchange research results and address open issues in all aspects of computational biology. PSB will provide a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. PSB intends to attract a balanced combination of computer scientists and biologists, presenting significant original research, demonstrating computer systems, and facilitating formal and informal discussions on topics of importance to computational biology.

To provide focus for the very broad area of biological computing, PSB is organized into a series of specific sessions. Each session will involve both formal research presentations and open discussion groups.


  • Advanced Methods for Big Data Analytics in Women's Health
  • Achieving Trustworthy Biomedical Data
  • Pattern Recognition in Biomedical Data for Discovery
  • What about the environment? Leveraging multi-omic datasets to characterize the environment’s role in human health
  • Biocomputing and AI for infectious disease modelling and therapeutics
  • Computational Challenges and Artificial Intelligence in Precision Medicine