Paper Info
Title
Computational Intelligence for Life Sciences.
Abstract
Computational Intelligence (CI) is a computer science discipline encompassing the theory, design, development and application of biologically and linguistically derived computational paradigms. Traditionally, the main elements of CI are Evolutionary Computation, Swarm Intelligence, Fuzzy Logic, and Neural Networks. CI aims at proposing new algorithms able to solve complex computational problems by taking inspiration from natural phenomena. In an intriguing turn of events, these nature-inspired methods have been widely adopted to investigate a plethora of problems related to nature itself. In this paper we present a variety of CI methods applied to three problems in life sciences, highlighting their effectiveness: we describe how protein folding can be faced by exploiting Genetic Programming, the inference of haplotypes can be tackled using Genetic Algorithms, and the estimation of biochemical kinetic parameters can be performed by means of Swarm Intelligence. We show that CI methods can generate very high quality solutions, providing a sound methodology to solve complex optimization problems in life sciences.
Year
DOI
Venue
2020
10.3233/FI-2020-1872
FUNDAMENTA INFORMATICAE
Keywords
Field
DocType
Computational Intelligence,Evolutionary Computation,Swarm Intelligence,Genetic Programming,Genetic Algorithm,Particle Swarm Optimization,Protein Folding,Haplotype Assembly,Parameter Estimation
Discrete mathematics,Computational intelligence,Mathematics education,Mathematics
Journal
Volume
Issue
ISSN
171
SP1-4
0169-2968
Citations 
PageRank 
References 
0
0.34
0
Authors
10
Name
Order
Citations
PageRank
Daniela Besozzi139139.10
Luca Manzoni248855.19
Marco S. Nobile314323.69
Simone Spolaor400.34
Mauro Castelli559556.31
Leonardo Vanneschi61440116.04
Paolo Cazzaniga723527.16
Stefano Ruberto8192.59
Leonardo Rundo9256.40
Andrea Tangherloni10407.88