Research areas
We work on algorithm development for homolog identification, multiple sequence alignment, phylogenetic tree construction, protein fold prediction, identification of domain boundaries (and novel domains), and detection of key amino acids, such as catalytic or binding pocket residues. Structure prediction methods have obvious implications on the inference of protein function, as protein function is mediated by protein fold. Because evolution conserves structure in order to conserve function, we integrate phylogenetic tree construction and subfamily identification into our protein structure and function prediction methods, to enable us to infer the changes produced in protein function and structure over the evolution of a protein superfamily.
Some specific projects include the following:
Computational Method Development
Clustering and alignment
Phylogenetic tree inference
Identifying key functional positions
Domain Identification
Constructing homology models
Profile-profile scoring and alignment
Protein structure prediction and HMM methods in general
Biological Investigation
Animal proteome analysis and functional annotation of animal genomes
Plant proteome analysis and functional annotation of plant genomes
Trans-kingdom Innate Immunity
Protein Superfamily Evolution
User Interface and Webserver/Database Development
HMM library development
Graphical user interfaces for phylogenomic inference
Student Research Opportunities
These are available for qualified students. These are of two basic types.
The first type of rotation involves algorithm (computational method) development for problems in molecular biology. Students interested in this type of rotation should have solid programming skills (i.e., C/C++/Java and Perl or Python).
The second type of rotation involves using informatics methods to predict protein function or structure, typically in collaboration with biologists here on campus.
Students interested in this latter type of rotation need some solid coursework in molecular biology, and should preferably have taken Bioengineering 144, Introduction to Protein Informatics.
To apply, submit
a transcript of your grades at Berkeley (unofficial is acceptable),
the names and contact information for two references (faculty who know your work is best, TAs are acceptable), and
a brief description of your personal research interests, what kind of work you like to do, and your background in programming, mathematics, and biology.
