Current Status of Machine Learning Applications in Molecular Biology and Biological Signal Processing

Abstract

Data science is the study of extracting knowledge and making inferences from data. Various data science techniques have been developed to manage, process, and use big/heterogeneous data. The most successful technique is deep learning using neural networks. This paper first describes the current state of machine learning. It then presents two applications of machine learning are presented. The first is an application of machine learning in molecular biology, and the second is an application of machine learning in biological signal processing. The molecular biology application will mainly explain DNA methylation analysis will be explained. The biological signal processing application will mainly explain the classification and quantification of tremors.