Feature Selection, Machine Learning and Deep Learning Algorithms on Multi-modal Omics Data

Emergence of feature selection technique as a chronic and promising research topic has created profound impact on the advancement of bioinformatics in our techno-equipped society. Due to the significant role of feature selection strategy for the progression of research sphere of bioinformatics, various approaches of this strategy are widely used in several fields of biomedical research such as cancer research, COVID-19 detection and many more. Accomplishment of feature selection deals with the perception regarding machine learning as well as deep learning. In this regard, it is essential to possess the knowledge of employing appropriate approach among different implementing procedures of feature selection to the proper biomedical research domain. Feature selection technique is also regarded as a significant paradigm with a view to analyze gene expression data for biomarker discovery. This chapter demonstrates a comprehensive survey briefly on some existing research works regarding the application of feature selection employed using the notion of machine learning or deep learning accompanied by their beneficial aspects as well as limiting barriers in sphere of bioinformatics. Finally, it is expected that our study will be helpful for the enrichment of knowledge regarding existing research works based on feature selection in bio-medical field.