1Department of Biotechnology, Delhi Technological University, Delhi, India
2Department of Biotechnology, Graphic Era University, Dehradun, India
*Corresponding Author: Megha Bansal, Department of Biotechnology, Graphic Era University, Dehradun, India
Machine learning methodologies have been introduced into computational biology, which have radically changed the paradigms in biological research over the last decade. This paper analyzes the primary applications of machine learning in various fields of computational biology, including protein structure prediction, genomic sequence analysis, drug discovery, and systems biology. We evaluate the theoretical basis of these applications, their implementation, and the problems associated with applying computational learning algorithms to biological data. Special focus is given to deep learning structures that have proven exceptionally successful in the modelling of complex biological systems. We also examine recent developments, such as explainable artificial intelligence in medical biology, federated learning for conducting privacy-preserving medical studies, and the use of machine learning models to integrate multi-omics data. This thorough examination can present researchers with information on the existing methodologies, coupled with the promotion of prospective studies.
Keywords: Machine learning, computational biology, deep learning, protein structure prediction, drug discovery
How to cite this article: Shatrupa Singh, Anistha, Kanchan Yadav, Nilesh Yadav, Megha Bansal., Machine Learning in Computational Biology: Emerging Applications in Drug Discovery and Drug Delivery Systems..Int J Drug Deliv Technol. 2026;16(12s): 107-120. DOI: 10.25258/ijddt.16.12s.12
Source of support: Nil.
Conflict of interest: None