TJ Brunette

Lab Associations:

Laboratory for Perceptual Robotics
Bioinformatics Research Lab
The Gierasch's lab in BioChemistry

Contact Information:

Computer Science Department
University of Massachusetts, Amherst
Office: +1.413.545.3039
Fax: +1.413.545.1249
TJ(at)cs.umass.edu

Google map of where I work
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Education:

BS in Biochemistry SUNY Geneseo
Currently pursuing a M.S. and Ph.D. in Computer Science from UMass Amherst
in the Laboratory for Perceptual Robotics

Research:

The future of bioinformatics and biochemistry lies in the study of how three-dimensional biomolecules interact in the real world. Combining algorithms from machine learning, robotics, and computational geometry with methods from biochemistry will improve in silico simulation as well as suggest experimentation that maximizes knowledge gain while minimizing experimental cost. My first foray into this field is protein structure prediction. Protein structure prediction attempts to determine the three-dimensional structure of a protein based upon the primary amino acid sequence of the protein. Efficient computational approaches to structure determination represent a tool that can enable research to more quickly establish a protein's function, hence speeding drug discovery. Currently I am designing improved high dimensional search strategies motivated by motion-planning algorithms from the robotics domain, and drawing insights from active learning and taboo search. My algorithm is developed in the code package Rosetta, originally developed in Professor David Baker's laboratory. This is considered to be one of the most accurate protein prediction software in the world. Shown to the right is the results we have achieved with our improved search method for protein 2PTL. This protein consists of 60 amino acids and thus has 120 degrees of freedom. (2PTL really consists of 77 amino acids, but an extremely mobile tail has been cut off for the experiments.) Images shown correspond to the lowest energy conformation as scored by the software package Rosetta out of 500 decoys.

native structure-Determed via NMR predicted by Rosetta Predicted using our method Predicted by a better version of our method. The beta-sheets roll around the alpha-helix.

Publications:

Brunette, TJ and Oliver Brock. Improving Protein Structure Prediction with Model-Based Search. Bioinformatics 21(Suppl. 1):66-74, June 2005.Special Issue for the International Conference on Intelligent Systems for Molecular Biology (ISMB), Detoit, USA

Brunette, TJ and Oliver Brock. Model-Based Search to Determine Minima in Molecular Energy Landscapes. Technical Report 04-48. Computer Science Department, University of Massachusetts Amherst, September 2004.

J. Sweeney, TJ Brunette, Y. Yang, R. Grupen,Coordinated Teams of Reactive Mobile Platforms,in the Proceedings of the 2002 IEEE Conference on Robotics and Automation, Washington, D.C. May, 2002 © 2002 IEEE

Pictures:

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Curriculum Vitae

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