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Physical Sciences and Mathematics

University of Arkansas, Fayetteville

Computer Science and Computer Engineering Undergraduate Honors Theses

2016

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A Support Vector Machine Base Model For Predicting Heparin-Binding Proteins Using Biological Metrics And Xb Patterns As Features, Joseph W. Sirrianni May 2016

A Support Vector Machine Base Model For Predicting Heparin-Binding Proteins Using Biological Metrics And Xb Patterns As Features, Joseph W. Sirrianni

Computer Science and Computer Engineering Undergraduate Honors Theses

Heparin is a highly sulphated and negatively charged polysaccharides belonging to the glycosamino- glycans(GAGs) family. It is widely used in medical treatments as an injectable anticoagulant. Although many heparin-binding proteins have been identified through experimental studies, there are still many proteins needing to be classified as heparin-binding or not. Many studies have been aimed at prediction of heparin binding patterns or motifs in the primary structure of proteins. For example XBBXBX and XBBBXXBX are two well-known patterns or motifs. In spite of intensive studies, still no good model has emerged which reasonably predicts proteins in the protein database as heparin-binding …