Print This PageBobbie-Jo M. Webb-Robertson, Ph.D.
Expertise
Bobbie-Jo M. Webb-Robertson
Dr. Webb-Robertson's research interests includes the development of statistical inference models, largely Bayesian, with application to bioinformatics problems such as the analysis of protein structure and function, gene expression, and mutational properties of biological sequence data. Previous work includes the development of a novel algorithm that models sequence alignment as a Bayesian inference problem, Bayesian Algorithm for Local Sequence Alignment (BALSA), with application to protein homolog search and sequence reduction in search of regulatory regions of genes.
Education
- Ph.D., Decision Sciences and Engineering Systems, Rensselaer Polytechnic Institute, 2002
- M.E., Operations Research and Statistics, Rensselaer Polytechnic Institute, 2000
- B.A., Mathematics, Eastern Oregon University, 1997
Honors and Awards
- Program in Mathematics and Molecular Biology Fellowship, 8/99-7/01
- GE Future Faculty Scholarship, 8/99-7/00
- Induction to the Industrial Engineering Honor Society of Alpha Pi Mu, 3/99
- Chauncey and Doris Starr Graduate Fellowship, 8/97-5/98
- School of Engineering Topper Award, 8/97-5/98
Selected Publications
Webb BM, JS Liu, and CE Lawrence. 2002. "BALSA: A Bayesian algorithm for local sequence alignment." Nucleic Acids Research , 30(5):1268-1277.
Havre SL, M Singhal, DA Payne, MS Lipton, and BM Webb-Robertson. 2005. "Enabling proteomics discovery through visual analysis." IEEE Engineering in Medicine and Biology Magazine, Special Issue on Computational Approaches in Proteomics, 24(3):50-57.
Webb-Robertson BM, KH Jarman, SD Harvey, C Posse, and BW Wright. 2005. "An improved optimization algorithm and Bayes factor termination criterion for sequential projection pursuit." Chemometrics and Intelligent Laboratory Systems, 77(1-2): 149-160.
Cannon WR, KH Jarman, Webb-Robertson BM, DJ Baxter, CS Oehmen, KD Jarman, A Heredia-Langner and KJ Auberry. 2005. "Comparison of Probability and Likelihood Models for Peptide Identification from Tandem Mass Spectrometry. Journal of Proteome Research, 4(5): 1687-1698.
Webb-Robertson BM, CS Oehmen and MM Matzke. 2005 "Bayesian Alignment Improves Sensitivity for Protein Family Classification from Sequence Based Support Vector Machines." Computational Biology and Chemistry, 29(6): 440-443.
