William R. Cannon, Ph.D.
Research Interests

William Cannon
Dr. Cannon's primary interests are (1) statistical and biological inference of cellular networks from high-throughput DNA microarray and mass spectrometry/proteomic experiments, (2) analysis of mass spectrometry data, and (3) integration of diverse biological data into a comprehensive model of cellular function. His previous work includes DNA microarray analysis and method development, computational and experimental enzymology, and molecular simulations with regard to engineering enzymes for desired catalytic properties. He has 10 years of experience in software development in both industry and academia.
Education
- Ph.D., BioPhysics (Stat. Mech.), University of Houston, 1994
- B.A., Chemistry, University of California, 1983
Honors and Awards
- Monsanto Outstanding Research Award, 1999
- National Research Service Award, NIH Postdoctoral Fellow, 1995
- National Research Service Award, NIH Predoctoral Scholarship, 1990
Professional Societies
- International Society for Computational Biology
- American Chemical Society
Selected Publications
Cannon WR, SF Singleton, and SJ Benkovic. (1996). "A perspective on biological catalysis." Nature Structural Biology 3:821-833.
Cannon WR, and SJ Benkovic. (1998). "Solvation, Reorganization Energy and Biological Catalysis." J. Biol. Chem. 273:26257-26260.
Heredia-Langner A, WR Cannon, KD Jarman and KH Jarman. (2004). "Sequence Optimization as an Alternative to de novo Analysis of MS/MS Data," Bioinformatics, 20(14): p. 2296-2304.
Cannon WR, KH Jarman, BM Webb-Robertson, DJ Baxter, CS Oehmen, KD Jarman, A Heredia-Langner, GA Anderson, and KJ Auberry. (2005). "A Comparison of Probability and Likelihood Models for Peptide Identification from Tandem Mass Spectrometry Data," J. Proteome Res. 4(5):1687-1698.
Webb-Robertson, B.J., Cannon, W. R., Oehmen, C. S., Shah, A. R., Gurumoorthi, V., Lipton, M. S., Waters, K. M. (2008). "A Support Vector Machine model for the prediction of proteotypic peptides for accurate mass and time proteomics." Bioinformatics, 24(13); 1503-1509.
