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BIG DATA IN BIOLOGY SYMPOSIUM

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The 2nd Annual Symposium on Big Data in Biology (BDiB) will be held Friday May 16th, 2014, in NHB 1.720 on the UT campus. Hosted by the Center for Computational Biology and Bioinformatics and supported by the College of Natural Sciences Bioinformatics Initiative, this event showcases the excellent research done here at The University of Texas at Austin, including TACC (Texas Advanced Computing Center), that takes advantage of high throughput approaches, complex data and/or high performance computing.

Pamela Silver (SB, Harvard Medical School) will be the keynote speaker. Pamela builds cell-based machines, designing novel therapeutics, and reengineering photosynthetic bacteria to produce hydrogen and other fuels.

The symposium will provide an ideal opportunity registered attendees from UT Austin and nearby institutions with an interest in computational biology, bioinformatics, and systems biology to interact. A poster session following the symposium will allow trainees to explain their work and facilitate fruitful exchanges. There will also be a breakout session during the lunch period to discuss such topics as: Big Data in Undergraduate Teaching, Industry Career Panel, and Big Data in Medicine.

The program is listed below. You may also download it here.

2nd Annual Symposium on Big Data in Biology
Friday, May 16, 2014
NHB 1.720

08:45 Breakfast

09:15 Opening remarks: Hans Hofmann (Director, Center for Computational Biology & Bioinformatics)

09:25 Rosalind Eggo (Statistics and Data Sciences)
Epidemics of the "common cold" and the dynamics of severe asthma exacerbations

09:50 Claudio Casola (Texas A&M University)
Interlocus gene conversion and gene evolution in eukaryotes

10:15 Claus Wilke (Integrative Biology)
Biophysical perspectives on molecular evolution

10:40 Coffee break

11:00 Keynote Lecture: Pamela Silver (Harvard Medical School)
Designing Biological Circuits

12:00 Lunch Breakout Sessions*
Topics: Big Data in Undergraduate Teaching, Industry Career Panel, Big Data in Medicine

01:30 Vishy Iyer (Molecular Biosciences)
Transcriptional regulation of the human genome: Lessons from ENCODE and beyond

01:55 Elizabeth Milano (Integrative Biology)
The genetics of divergence between upland and lowland ecotypes of Panicum virgatum

02:10 Matthew Cowperthwaite (Texas Advanced Computing Center)
An eQTL analysis of the human glioblastoma multiforme genome.

02:35 Poster session (with coffee and refreshments)

05:00 Announcement of poster awards; closing remarks: Scott Hunicke-Smith (Genome Sequencing and Analysis Facility)

*Lunch Breakout Sessions:
Big Data in Biology and Undergraduate Teaching
Claus Wilke (Integrative Biology), Andy Ellington (Molecular Biosciences), Sarah Simmons (Freshman Research Initiative)
Big Data in Medicine
Lauren Meyers (Integrative Biology), Robert Messing (Vice Provost for Biomedical Sciences), Matthew Cowperthwaite (Texas Advanced Computing Center)
Industry Career Panel
Scott Hunicke-Smith (Director, Genome Sequencing and Analysis Facility), William Honea (T-Systems North America), Krista Ternus (Signature Science), Alex Adai (Asuragen)

If you have any questions regarding this year's symposium, please contact Nicole Elmer.

postersession

Big Data in Biology Poster Session from the 2013 symposium.

PriceTalk

Keynote speaker, Nathan Price, from the 2013 symposium.

 

 

MAKE A GIFT

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The vision of the CCBB is to provide an exciting intellectual environment, an excellent bioinformatics consulting group, an advanced computing infrastructure, and training opportunities in computational approaches to the fundamental questions of modern biology.

Given advances in sequencing technology, imaging, and remote sensing, we are faced with many opportunities for "Big Data Biology" in genomics, evolution, neuroscience, environmental science, etc. Yet at the same time challenges remain to be overcome if we want to gain insight and knowledge from vast amounts of information.

Join us as we work for our vision to become reality! As much of our research is at the leading edge of science, opportunities in Big Data Biology are simply impossible without your support for seed grants, professorships, and student/postdoctoral fellowships. This allows us to sustain activities not supported by University funds or grant monies.