Machine Learning in Bioinformatics
Bioinformatics is the application of computational techniques to analyze the information associated with biomolecules on a large-scale, has now firmly established itself as a discipline in molecular biology, and encompasses a wide range of subject areas from structural biology, genomics to gene expression studies. The availability of new, highly effective tools such as particular genomics, transcriptomics, proteomics and metabolomics for biological exploration is dramatically changing the way one performs research in bioinformatics. Taking advantage of this wealth of \"genomic\" information has become a norm for whoever ambitions to remain competitive in sciences in general. Machine learning naturally appears as one of the main drivers of progress in this context. In this review we provide an introduction and overview of the current state of the field. We discuss the main principles that underpin bioinformatics analyses using machine language.
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[Javed Mohammed (2014); Machine Learning in Bioinformatics Int. J. of Adv. Res. 2 (12). 0] (ISSN 2320-5407). www.journalijar.com
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