Professor, Computer Science and Engineering
Computational molecular biology, bioinformatics, proteomics, approximational algorithms, human genome, human proteome, protein identification, Expressed Sequence Tags (EST) analysis Professor Bafna is an expert in bioinformatics. He has published on many aspects of this emerging field, including genome rearrangements, multiple alignments, RNA structure, gene finding, DNA signals, mass spectrometric data analysis, and human population genetics. In genome rearrangement, he introduced (with his then-advisor and now UCSD colleague Pavel Pevzner) the breakpoint graph technique that is now commonly used when doing computational analysis of genome rearrangements. In computational proteomics, Bafna made key contributions to the problem of protein identification by devising a scoring function that incorporates ion fragmentation probability as well as instrument error, and an efficient algorithm to compute that score. He led a team at Celera that built a toolkit for identifying and quantitfying the Proteome using mass spectrometry.At UCSD, Vineet Bafna continues to focus on computational analysis of peptide mass spectra and applications to protein function, and analyzing data on single nucleotide polymorphisms (SNP), with applications to therapeutics and diagnostics. His ongoing algorithmic work on haplotype phasing will play an important role in the study of human genetic variations.Vineet Bafna has developed numerous toolkits for analyzing peptide sequences and other genomic data, including the Conserved Exon Method for gene finding (CEM) that uses conservation of coding regions in human and mouse genomes to simultaneously find gene structures in both species, and SCOPE and DiffXPro for identifying and quantifying proteins using mass spectrometry data.
Jacobs School Faculty Update Your Profile