This chapter presents a thorough background and deep literature review of the current topic of study. It also presents and defines the key concepts utilised throughout this investigation. It consists of ten sections: (1) a background on bioinformatics, (2) a discussion of colon cancer, (3) an overview of the microarray technology that is used to extract the dataset, (4) an overview of the colon cancer dataset, (5) a review of the most prevalent algorithms employed for gene selection and cancer classification, (6) a presentation of related works from the literature, (7) identification of feature selection approaches and procedures, (8) an investigation of the ML concept, (9) a review of algorithm efficiency and time complexity analysis, and (10) identification of current problems in the research area.
TopBioinformatics is the integration of the fields of biology, computer science, statistics, and mathematics (Al-Rajab & Lu, 2012), with each field playing a significant role in gathering, forming, analysing, and digitising genetic data. Moreover, it aids the efficient categorisation and storage of data (Al-Rajab & Lu, 2012; Bayat, 2002; Cohen, 2005; Jawdat, 2006; Jena et al., 2009; Ng & Wong, 2004).
Bioinformatics was first introduced in 1979 by Paulien Hogeweg to study the informatic procedures of biological systems (Raza, 2012). This section elaborates bioinformatics using a variety of scientific papers to establish the basis for the current research, to identify core bioinformatics applications, to present the data structure and the central databases employed, to provide an overview of the most popular algorithms applied to this field, and to advocate for the employment of bioinformatics in the area of cancer research.