William R Cannon
Affiliations: | Pacific Northwest National Laboratory, Richland, WA, United States |
Area:
BiophysicsGoogle:
"William Cannon"Mean distance: (not calculated yet)
Parents
Sign in to add mentor| J. Andrew McCammon | grad student | UCSD | |
| Stephen J. Benkovic | post-doc | Penn State |
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Publications
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| Cannon W, Baker S. (2017) Non-steady state mass action dynamics without rate constants: dynamics of coupled reactions using chemical potentials. Physical Biology |
| Cannon WR. (2014) Concepts, challenges, and successes in modeling thermodynamics of metabolism. Frontiers in Bioengineering and Biotechnology. 2: 53 |
| Thomas DG, Jaramillo-Riveri S, Baxter DJ, et al. (2014) Comparison of Optimal Thermodynamic Models of the Tricarboxylic Acid Cycle from Heterotrophs, Cyanobacteria, and Green Sulfur Bacteria. The Journal of Physical Chemistry. B |
| Cannon WR. (2014) Simulating metabolism with statistical thermodynamics Plos One. 9 |
| Kalyanaraman A, Cannon WR, Latt B, et al. (2011) MapReduce implementation of a hybrid spectral library-database search method for large-scale peptide identification. Bioinformatics (Oxford, England). 27: 3072-3 |
| Cannon WR, Rawlins MM, Baxter DJ, et al. (2011) Large improvements in MS/MS-based peptide identification rates using a hybrid analysis. Journal of Proteome Research. 10: 2306-17 |
| Cannon WR, Rawlins MM. (2010) Physicochemical/thermodynamic framework for the interpretation of peptide tandem mass spectra Journal of Physical Chemistry C. 114: 5360-5366 |
| Cannon WR, Taasevigen D, Baxter DJ, et al. (2007) Evaluation of the influence of amino acid composition on the propensity for collision-induced dissociation of model peptides using molecular dynamics simulations. Journal of the American Society For Mass Spectrometry. 18: 1625-37 |
| Webb-Robertson BJ, Cannon WR. (2007) Current trends in computational inference from mass spectrometry-based proteomics. Briefings in Bioinformatics. 8: 304-17 |
| Cannon WR, Jarman KH, Webb-Robertson BJ, et al. (2005) Comparison of probability and likelihood models for peptide identification from tandem mass spectrometry data. Journal of Proteome Research. 4: 1687-98 |