A Literature Survey on Bioinformatics

Abstract: The area of Bioinformatics has arisen from the needs of biologists to utilize and interpret the vast amounts of data that are constantly being gathered in genomics research. The ultimate goal of bioinformatics is to develop in silico models that will complement in vitro and in vivo biological experiments. Bioinformatics encompasses the development of databases to store and retrieve biological data, of algorithms and statistics to analyze and determine relationships in biological data, and of statistical tools to identify, interpret, and mine datasets. Database management, artificial intelligence, data mining, and knowledge representation can provide key solutions to the challenges posed by biological data. AI in bioinformatics provides both basic as well as clinical research with the help of biological sequence matching, proteinprotein interaction and function-structure analysis. This analysis helps in the design and discovery of drugs as well as complex systems. Deep learning (DL) has shown explosive growth in its application to bioinformatics and has demonstrated thrillingly promising power to mine the complex relationship hidden in large-scale biological and biomedical data.

Keywords: Bioinformatics, Data mining, Artificial Intelligence, Deep learning