Yana Bromberg

Biography

I am currently working as a Associate Professor in Department of Biochemistry and Microbiology in Rutgers University

Research Interest

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).