OCCBIO 2010 Home

Program

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Exhibitors

Accomodations

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Conference Organizers

The Ohio State University

OSU Department of Biomedical Informatics (BMI)

Directions

State Route 315 Project Info

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Printed Materials

Poster [pdf]

Brochure [pdf]

Call for Abstracts [pdf]

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Ohio Collaborative Conference on Bioinformatics 2010

The fifth annual Ohio Collaborative Conference on Bioinformatics was hosted by the Ohio State University in Columbus, Ohio in the Ohio Union June 15-17, 2010.

Conference Program

Keynote Speakers

Day 1: Tuesday- June 15, 2010
Ward Wheeler, American Museum of Natural History
Title: Evolutionary Genomics & Infectious Diseases

Wolfgang Sadee, The Ohio State University
Title: Personalized Medicine

Day 2: Wednesday - June 16, 2010
Fritz Roth, Harvard University
Title: Biological Networks

Mark Gerstein, Yale University
Title: Structural Bioinformatics

Day 3: Thursday - June 17, 2010
Tim Huang, The Ohio State University
Title: Sequence Analysis

The conference provided an interdisciplinary forum for the discussion of methods, research findings, and experiences.

An important goal for the conference was to foster long-term collaborative relationships and networking opportunities within the domain of computational approaches to biology that benefit Ohio.

The Ohio Collaborative Conference on Bioinformatics (OCCBIO) is supported by the Ohio Bioinformatics Consortium (link name to OBC page) which strives to enhance educational opportunities and research infrastructure throughout the state to make Ohio a world leader in bioinformatics and to facilitate new discoveries in data-intensive biomedical research.

The Challenge

Due to the wealth of information being created, and much more on the way, both bioinformatic and statistical analyses have become a serious bottleneck. This is due to a need for more broadly educated and computationally skilled people who are able to understand the biological principles behind the data, engage in multi-disciplinary talk, and generally make sense of the data being collected.