On about What Can Be Done and What Cannot Be Done with Genetic Algorithms in Phylogenetic Tree and Gene Sequence Analyses

Genetic algorithms, a sort of algorithms belonging to a more general category, so called meta-heuristics, know today a great expansion in terms of target applications, including biology, chemistry and medicine. They are inspired from primary observations in nature (Lamarck, 1809; Darwin, 1859; Mendel, 1865; Fisher, 1918), and started with simulation of artificial selection of organisms with multiple loci that controls a measurable trait (Fraser, 1957). Genetic algorithms evolved into complex and strong informatics tools capable to deal with hard problems of decision, classification, optimization, and simulation in fields as biology, chemistry and medicine. The aim of the present article was to introduce genetic algorithms and to present their suitability for biological hard problems. Some important results reported in the literature about the use of genetic algorithms for phylogenetic and gene sequence analysis are discussed.