Similitud funcional de genes basada en conocimiento biológico

Abstract

Over the last few year, our knowledge about biological processes in living organisms has greatly expanded both in quantity and resolution, mostly thanks to the introduction of high-throughput sequencing technology. Making sense of these vast amount of biological data through methods such as automated learning is therefore critical to gain further insights into the molecular mechanisms behind fundamental biological processes.

This work aims at establishing the quality of new genetic model based on actual biological data. First, a tool for analyzing the coherence of a group of genes according to their common role in metabolic processes is developed. This tool allows the evaluation and validation of different gene sets obtained through any clustering technique.

Additionally, a novel measure of functional similarity of a group of genes has been introduced. This measure, called GFD, is based on the Gene Ontology, and it assigns a numerical value to a gene set for each of the three GO ontologies. Concretely, GFD computes the similarity based only on the most common and specific functionality of the genes. GFD compre favorably against the most relevant measures. Our approach is especially relevant in the study of genes that are involved in several functions.