Introduction of Reinforcement Learning in Bioinformatics

Unprecedented and never seen moves in chess by artificial intelligence computer program alphago reveal the first true success of reinforcement learning. Since then researchers from across the disciplines got attention and exploring the potential to solve some not looking possible challenges. Extracting inherent valuable knowledge from omics data remains as a daunting problem in bioinformatics. Bioinformatics got huge boost with the advancement of artificial intelligence, such as image analysis for disease prediction, protein structure analysis etc. Reinforcement learning is a type of artificial intelligence technique comes under machine learning. Nature of Reinforcement learning approaches and dynamicity of a cell hold similar features and hence these approaches have tremendous potential which can be used to solve biological problems. In this article, we have highlighted some of the major challenges decoded using reinforcement learning for the application in bioinformatics and its future prospective.