Final Oral - Kejue Jia - " Using evolutionary covariance to infer protein sequence-structure relationships"

Event
Monday, November 12, 2018 - 11:00am to 1:00pm

Major professors: Drena Dobbs and Robert Jernigan

Committee Members - Guang Song, Zhijun Wu and Huaiqing Wu

Title of Defense:
   Using evolutionary covariance to infer protein sequence-structure relationships

Abstract:
   Learning about the relationships among protein sequence, structure and dynamics becomes one of the most important steps for understanding the mechanisms of proteins. Together with the rapid growth in the efficiency of computers, there has been a commensurate growth in the sizes of the public databases for proteins. The field of computational biology has undergone a paradigm shift from investigating single proteins to looking collectively at sets of related proteins and broadly across all proteins. we develop a novel approach that combines the structure knowledge from the PDB, the CATH database with sequence information from the Pfam database by using co-evolution in sequences to achieve the following goals: (a) Collection of co-evolution information on the large scale by using protein domain family data; (b) Development of novel amino acid substitution matrices based on the structural information incorporated; (c) Higher order co-evolution correlation detection.

 

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