AN EMPIRICAL SCIENCE RESEARCH ON BIOINFORMATICS IN MACHINE LEARNING

Abstract

The subset of Artificial Intelligence (AI) is Machine Learning. Machine Learning (ML) has a rapid growth in all fields of research such as medical, bio-surveillance, robotics and all other industrial applications. Improvements in accuracy and efficiency of ML techniques in bio-informatics have steadily increased for solving problems in medicine. The aim of this paper is to give brief note about applications of ML in bio-informatics and science research. Bioinformatics involves the interaction of biology, computer science and statistics. In bioinformatics, Data were extracted, analyzed and classified for the prediction of various diseases. This process is time consuming and expensive. To reduce the cost and time, traditional techniques for extracting and analyzing the data were replaced by machine learning techniques.