Computation in BioInformatics

9Machine Learning in Bioinformatics

Rahul Yadav¹, Mohit Sharma^2,3 and Nikhil Agrawal⁴*

¹SRM University, SRM Nagar, Kattankulathur, Tamil Nadu, India

²Postgraduate School for Molecular Medicine, Medical University of Warsaw, Warszawa, Poland

³Poland Malopolskie Centre of Biotechnology Jagiellonian University, Krakow, Poland

⁴College of Health Sciences, University of KwaZulu-Natal, Westville, Durban, South Africa

Abstract

Human evolution has seen different stages, and at present, we are in the information Age. The revolution to this age started with the advent of the internet. In the present age, data is generated in huge amount in different domains of science. Specially, in biological sciences e.g., genomics, proteomics, molecular modeling etc. The data generated for genomics different from that of molecular modeling. However, the information’s can be linked to obtain a better insight into the functionality even at the cellular level. It has become tough to analyze such massive data and conclude in a short period. The present-day scenario is changing with the implementation of Machine Learning methods. Machine Learning provides more in-depth insight into the problems backed up by mathematically models to take a short amount of time in terms of analysis. Machine Learning has been implemented in detection and medication suggestions for cancer patients. In drug discovery, Machine Learning models have been developed to design potential drug molecules. In the present chapter, we ...