Biological Data Mining: Discovering Knowledge in the Age of Big Biology

Ramesh Krishnamoorthy^1*, Karthik M²

Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India

*Corresponding Author

Ramesh Krishnamoorthy, Department of Computer Science and Engineering, Bharath Institute of Higher Education and Research, Chennai, Tamil Nadu, India, E-mail: r_krishnamoorthy@gmail.com

Abstract

Biological data mining is a key interdisciplinary field that applies computational techniques to uncover patterns, associations, and insights from complex biological datasets. Driven by advances in high-throughput technologies such as next-generation sequencing, microarrays, and proteomics, biology has become a data-rich science. Data mining techniques—such as classification, clustering, association analysis, and machine learning—enable researchers to interpret these large datasets effectively. This article explores the foundations, techniques, applications, and challenges of biological data mining, highlighting how it contributes to areas such as genomics, systems biology, drug discovery, and personalized medicine.