Computer Engineering Commons^™

Improved Machine Learning Method For Analysis Of Gas Phase Chemistry Of Peptides, Allison Gehrke, Shaojun Sun, Lukasz Kurgan, Natalie Ahn, Katheryn Resing, Karen Kafadar, Kryzysztof Cios

Computer Science Publications

Background

Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) of peptides from complex digests with theoretically derived spectra from a database of protein sequences. Improved discrimination is achieved with theoretical spectra that are based on simulating gas phase chemistry of the peptides, but the limited understanding of those processes affects the accuracy of predictions from theoretical spectra.

Results

We employed a robust data mining strategy using new feature annotation functions of MAE software, which revealed under-prediction of the frequency of occurrence in fragmentation of the second peptide bond. We …

Scpred: Accurate Prediction Of Protein Structural Class For Sequences Of Twilight-Zone Similarity With Predicting Sequences, Lukasz Kurgan, Kryzysztof Cios, Ke Chen

Computer Science Publications

Background

Protein structure prediction methods provide accurate results when a homologous protein is predicted, while poorer predictions are obtained in the absence of homologous templates. However, some protein chains that share twilight-zone pairwise identity can form similar folds and thus determining structural similarity without the sequence similarity would be desirable for the structure prediction. The folding type of a protein or its domain is defined as the structural class. Current structural class prediction methods that predict the four structural classes defined in SCOP provide up to 63% accuracy for the datasets in which sequence identity of any pair of sequences …