 |
Yana Bromberg
Assistant Professor
Rutgers University
Dept. of Biochemistry and Microbiology
School of Env & Biol Sciences
Lipman Hall. Room 218
76 Lipman Drive
New Brunswick. N. J. 08901-0231
(848) 932-5638
FAX - 8965
yanab@rci.rutgers.edu |
Bioinformatics approaches to protein function prediction
and genome variation analysis
Modern biology increasingly relies on high-throughput
techniques. This trend challenges computational biologists to
quickly extract as much useful information from the data as
possible. In the genomic sense, this primarily implies correlating
phenotypic differences with observed nucleotide sequence
variations. On the protein side the challenge generally is to
annotate protein function at reasonable accuracy levels. We
believe that nucleic and amino acid sequences contain a large
portion of the information necessary to address both of these
directions.
Our main goal is to develop fast, accurate, and meaningful ways of
analyzing this growing deluge of biological data and to bring
these developments bench- (or patient-) side. To make our
predictions we rely on a number of sequence-based features
(including evolutionary information and other predictor results)
and utilize a variety of methodologies (including Neural Nets,
SVMs and random forests).
The active projects in the lab include:
- Development of an in silico mutagenesis methodology which will
define functionally important residues in protein sequences. This
direction addresses questions in nsSNP analysis, mutation combinatorics
(possibly applicable to phylogenetics), and function prediction.
- Analyzing the effects of genomic SNPs (non-coding or synonymous) on
the overall organism fitness. Initial steps in this direction focus on
data collection and on outlining SNP characteristics that can be used to
differentiate between functionally non-/important SNPs.
- Computational literature analysis (Natural Language
Processing) to extract from free text (scientific publications, lab
records, etc.) information relevant to the above two goals.
|
