A Survey on Applications of Machine Learning in Bioinformatics and Neuroscience

Machine learning is one of the most practical branches of artificial intelligence that tries to provide algorithms by which the system can analyze a set of data in different formats. Machine learning algorithms are widely used in biomedicine, bioinformatics and neuroscience. The main goal of this paper is to propose the latest applications of machine learning in bioinformatics and neural imaging and to introduce new branches of research. In this article, the application of four indicators of machine learning techniques in the field of bioinformatics is examined. The four categories of techniques studied include clustering, classification, dimensionality, and deep learning. In this paper, we also show that machine learning techniques can be successfully used to address common bioinformatics challenges such as gene expression, DNA methylation identification, mRNA expression, patient classification, brain network analysis, protein chain identification, clustering, and biomarker identification. In each section, some efficient articles with technical details are discussed separately. The results of some papers are also reported in terms of accuracy, database and techniques used.