Computational Intelligence in Solving Bioinformatics Problems: Reviews, Perspectives, and Challenges

Abstract

Summary. This chapter presents a broad overview of Computational Intelligence (CI) techniques including Artificial Neural Networks (ANN), Particle Swarm Optimization (PSO), Genetic Algorithms (GA), Fuzzy Sets (FS), and Rough Sets (RS). We review a number of applications of computational intelligence to problems in bioinformatics and computational biology, including gene expression, gene selection, cancer classification, protein function prediction, multiple sequence alignment, and DNA fragment assembly. We discuss some representative methods to provide inspiring examples to illustrate how CI could be applied to solve bioinformatic problems and how bioinformatics could be analyzed, processed, and characterized by computational intelligence. Challenges to be addressed and future directions of research are presented. An extensive bibliography is also included.

Artificial Intelligence and Bioinformatics

“…We have made a selection that we hope is representative of the variety of themes, trying each time to give the basics necessary to understand a specific problem, a formalization of this problem and a few achievements and progresses in relation to this problem. People interested in further reading could consult general reviews like [Hassanien et al, 2008[Hassanien et al, , 2013 or articles that are oriented towards a particular subfield of AI such as agents [Keedwell and Narayanan, 2005;Merelli et al, 2007] or knowledge discovery [Holzinger et al, 2014]. For the field of Bioinformatics itself many introductory texts exist, see for instance [Singh, 2015;Ramsden, 2004].…”

Bioinformatics: Strategies, Trends, and Perspectives

“…So, it is necessary to propose alternatives to treat a problem in a more efficient manner, developing strategies to attack it properly. In last years, Natural Computing methods have been applied to many fields of Bioinformatics (Fogel, 2008;Hassanien et al, 2008;Masulli & Mitra, 2009), such as protein structure prediction, protein folding simulation, microarray data analysis, and gene regulatory networks modeling. Natural Computing is a branch of the Computational Intelligence area that extracts ideas from nature to develop computational systems for problem solving which is related to optimization, data processing, and analysis techniques.…”

Adaptation of cuckoo search algorithm for the Motif Finding problem

“…The Swarm Intelligence (SI) is a recent emerging approach that is currently used to solve many problems including optimization problems similar to the motif finding problem. It has the ability to handle problems that are very complex in the field of Bioinformatics and Computational Biology [12]. In this paper, the features of the cuckoo search as a new promising swarm intelligence algorithm is adopted to solve the Planted Motif Finding Problem.…”