This press release is available in Spanish.
Proteins are molecules that are formed by chains of amino acids and they play a fundamental role in all of life, given that they contain the coded information in genes; they, therefore, carry out numerous functions in an organism: immunological (antibodies), structural (they constitute the majority of cellular material), bioregulating (they form part of enzymes) and a long list of etceteras. In short, they regulate thousands of process that take place within all organisms, including inside the human organism, and they frequently do so by means of relationships they establish with other cells. "Analyzing and using this network of interactions is a very interesting task due to the large number of associations that exist and to the multiple forms in which one protein can influence the function of others," explains Professor Beatriz Garca, of UC3M's Computer Science department. "In such a complex biological scenario, determining the functional associations through experiments is very costly, so we have tried to apply computational tools to predict these functions and so orient experimentation," she points out. Thus, the idea is to use techniques from the field of Artificial Intelligence, specifically from the area of Machine Learning, to obtain useful results for Biology, as part of an emerging interdisciplinary field known as Biocomputing or Computational Biology.
In this context, this line of research goes further in the annotation of the function of proteins, that is, in the determination of which protein or which group of proteins performs which task within an organism. In short, these scientists have dealt with two specific problems: the prediction of functional associations between pairs of proteins in the bacteria Escherichia coli and the extension of biological pathways in humans. In addition,
|Contact: Ana Herrera|
Carlos III University of Madrid