Improved Protein Function Classification Using Support Vector Machine

Abstract-Machine learning technique is introduced as a method for the classification of proteins into functionally distinguished classes. Protein function classification is one of the most important problems in modern computational biology. Studies are conducted on a number of protein classes including RNA-binding proteins; protein homodimers, proteins responsible for drug absorption, proteins involved in drug distribution and excretion, and drug metabolizing enzymes. Support vector machine in drug discoveries and designing based on two data sets of protein with their various physic-chemical properties. Some binary classification problems do not have a simple hyper plane as a useful separating criterion. For those problems, there is a variant of the mathematical approach that retains nearly all the simplicity of an SVM separating hyper plane. Th