This annual symposium provides an ideal opportunity for registered attendees from UT Austin and nearby institutions with an interest in computational biology, bioinformatics, and systems biology to interact. A poster session follows the symposium and allows trainees to explain their work and facilitate fruitful exchanges. 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.

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


Third Annual Symposium on Big Data in Biology

Friday, May 15th, 2015 Stay tuned for more information!

Event is being organized by The Transdisciplinary Big Data Scientist, a graduate student organization. Contact Rayna Harris if you are interested in joining the organization and/or helping with the event.


Second Annual Symposium on Big Data in Biology

Friday, May 16th, 2014 [Program] [Poster]

Edward Marcotte (Molecular Biosciences - UT Austin) was keynote speaker. Breakout sessions included topics such as : Big Data in Undergraduate Teaching, Industry Career Panel, and Big Data in Medicine.


First Annual Symposium on Big Data in Biology

Friday, May 10th, 2013 [Program] [Poster 1] [Poster 2]

Nathan Price (Institute for Systems Biology) was keynote speaker, with talk title "Harnessing Big Data for Biological and Medical Discovery."



Big Data in Biology Poster Session.


Keynote speaker, Nathan Price, from the 2013 symposium.



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.