Analyzing Protein Structure and Exploring the Sequence of Protein using Machine Learning Approach

Abstract

Protein structure and sequence analysis is an important and essential problem. Now machine learning techniques have been widely used in bioinformatics. In this research we analyze the protein of structure and sequence and predict the class of protein sequence. Also find the accuracy of that class for different machine learning algorithm. For the data set we use the exploratory data analysis (EDA) and extracted 278866 protein features from the data set. We classify the features and measure the accuracy level of the three machine learning algorithm: Support Vector Machine (SVM), Naive Bayes and Random Forest (RF) approach for that protein sequence.