Search Results - "Oehmen, C.S."

High-throughput computation of pairwise sequence similarities for multiple genome comparisons using ScalaBLAST by Shah, A.R., Markowitz, V.M., Oehmen, C.S.

“…Genome sequence comparisons of exponentially growing data sets form the foundation for the comparative analysis tools provided by community biological data…”
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Dimension Reduction via Unsupervised Learning Yields Significant Computational Improvements for Support Vector Machine Based Protein Family Classification by Webb-Robertson, B.-J.M., Matzke, M.M., Oehmen, C.S.

“…Reducing the dimension of vectors used in training support vector machines (SVMs) results in a proportional speedup in training time. For large-scale problems…”
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Support Vector Machine Classification of Probability Models and Peptide Features for Improved Peptide Identification from Shotgun Proteomics by Webb-Robertson, B.-J.M., Oehmen, C.S., Cannon, W.R.

“…Mass spectrometry (MS)-based proteomics is a powerful and popular high-throughput process for characterizing the global protein content of a sample. In shotgun…”
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Three distinct types of pacemaker cells in the sinoatrial node: computer simulations by Oehmen, C.S., Demir, S.S.

“…Based on recent experimental data, the rapid and slow potassium currents (I/sub Kr/ and I/sub Ks/, respectively) were incorporated into the rabbit sinoatrial…”
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Rapid and slow potassium currents in a sinoatrial node cell model by Oehmen, C.S., Demir, S.S.

“…The sinoatrial node (SAN) model of Demir et al. (Amer. J. Physiol, vol. 266, p. C832-52, 1994) was extended to include two potassium channels. A channel with…”
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