Fuzzy inference to decision support for SNP discovery

A single difference between base pairs of different aligned sequences is the most common type of genetic variability and it are called Single Nucleotide Polymorphisms (SNPs). They are crucial for the study of species variability, since they can cause functional or phenotypic modifications which, in turn, may imply in evolutionary or biochemical consequences in the individuals of a given species. SNPs discovery is made through several mathematical and computational models. This paper presents a model which uses fuzzy logic as the basis for the development of an inference system to aid decision making, which is based on previous results obtained by different SNP discovery tools and which present possibly conflicting results.