Open AccessA Study on machine learning methods and applications in genetics and genomics
Author(s) -
K. Jayanthi,
C. Mahesh
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.7.10653
Subject(s) - genomics , artificial intelligence , computer science , machine learning , set (abstract data type) , unsupervised learning , gene ontology , functional genomics , computational genomics , gene , genome , biology , gene expression , genetics , programming language
Machine learning enables computers to help humans in analysing knowledge from large, complex data sets. One of the complex data is genetics and genomic data which needs to analyse various set of functions automatically by the computers. Hope this machine learning methods can provide more useful for making these data for further usage like gene prediction, gene expression, gene ontology, gene finding, gene editing and etc. The purpose of this study is to explore some machine learning applications and algorithms to genetic and genomic data. At the end of this study we conclude the following topics classifications of machine learning problems: supervised, unsupervised and semi supervised, which type of method is suitable for various problems in genomics, applications of machine learning and future views of machine learning in genomics.