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Publications of Author

1. Christopher S. Oehmen, Lee Ann McCue, Joshua N. Adkins, Katrina M. Waters, Tim Carlson, William R. Cannon, Bobbie-Jo M. Webb-Robertson, Douglas J. Baxter, Elena Peterson, Mudita Singhal, Anuj R. Shah, Kyle R. Klicker
   Analytics challenge - High-throughput visual analytics biological sciences: turning data into knowledge. [Citation Graph (0, 0)][DBLP]
   SC, 2006, pp:299- [Conf]
   
2. Christopher S. Oehmen, Douglas J. Baxter, Ryan W. Mooney, Shaun O'Leary, Tim Carlson
   Bandwidth challenge - High throughput feature-matching analysis of biological spectral data. [Citation Graph (0, 0)][DBLP]
   SC, 2006, pp:243- [Conf]
   
3. Bobbie-Jo M. Webb-Robertson, Christopher S. Oehmen, Melissa Matzke
   SVM-BALSA: Remote homology detection based on Bayesian sequence alignment. [Citation Graph (0, 0)][DBLP]
   Computational Biology and Chemistry, 2005, v:29, n:6, pp:440-443 [Journal]
   
4. Anuj R. Shah, Christopher S. Oehmen, Jill Harper, Bobbie-Jo M. Webb-Robertson
   Integrating subcellular location for improving machine learning models of remote homology detection in eukaryotic organisms. [Citation Graph (0, 0)][DBLP]
   Computational Biology and Chemistry, 2007, v:31, n:2, pp:138-142 [Journal]
   
5. 
   Dimension Reduction via Unsupervised Learning Yields Significant Computational Improvements for Support Vector Machine Based Protein Family Classification. [Citation Graph (, )][DBLP]
   
   
6. 
   Support Vector Machine Classification of Probability Models and Peptide Features for Improved Peptide Identification from Shotgun Proteomics. [Citation Graph (, )][DBLP]
   
   
7. 
   PQuad - a visual analysis platform for proteomic data exploration of microbial organisms. [Citation Graph (, )][DBLP]
   
   
8. 
   SVM-HUSTLE - an iterative semi-supervised machine learning approach for pairwise protein remote homology detection. [Citation Graph (, )][DBLP]
   
   
9. 
   A support vector machine model for the prediction of proteotypic peptides for accurate mass and time proteomics. [Citation Graph (, )][DBLP]
   
   
10. 
    A support vector machine model for the prediction of proteotypic peptides for accurate mass and time proteomics. [Citation Graph (, )][DBLP]
    
    
11. 
    Physicochemical property distributions for accurate and rapid pairwise protein homology detection. [Citation Graph (, )][DBLP]
    
    
12. 
    A feature vector integration approach for a generalized support vector machine pairwise homology algorithm. [Citation Graph (, )][DBLP]