Introduction to Bioinformatics and Machine Learning

Abstract

ML has revolutionised bioinformatics' difficult biological data analysis. Pattern recognition and biological process categorization help ML systems diagnose diseases, predict protein structures, and investigate gene expression. Few-shot learning and bioinformatics are effective at optimising results with limited resources, overcoming biological dataset access issues. ML and bioinformatics advance precision medicine and drug discovery while improving biological understanding. This chapter examines bioinformatics ML methods like supervised classification, clustering, and probabilistic graphical models to find new insights. Text mining, systems biology, evolution, proteomics, and genomics use deterministic and stochastic heuristics for optimisation. Understanding bioinformatics methods and modern ML technologies while understanding implementation challenges is the study goal. Few-shot learning is highlighted to show its importance. ML and bioinformatics together improve our knowledge and solve real problems, improving research methods in biological and medical sciences.