title: Biological network querying techniques: analysis and comparison.
abstract: Research in systems biology has made available large amounts of data about interactions among cell building blocks (e.g., proteins, genes). To properly look up these data and mine useful information, the design and development of automatic tools has become crucial. These tools leverage Biological Networks as a formal model to encode molecular interactions. Biological networks can be fed as input to graph-based techniques useful to infer new information about cellular activity and evolutive processes of the species. In this context, a rather interesting family of techniques is that of network querying. Network querying tools search a whole biological network to identify conserved occurrences of a given query module for transferring biological knowledge. Indeed, inasmuch as the query network generally encodes a well-characterized functional module, its occurrences in the queried network suggest that the latter (and, as such, the corresponding organism) features the function encoded by the former. The aim of this paper is that of analyzing and comparing tools devised to query biological networks. This analysis is intended to help in understanding problems and research issues, state of the art and opportunities for researchers working in this area.
authors.affiliation: Faculty of Computer Science, Free University of Bozen-Bolzano, Bozen-Bolzano, Italy. valeria.fionda@unibz.it
authors.forename: Valeria
authors.initials: V
authors.lastname: Fionda
authors.forename: Luigi
authors.initials: L
authors.lastname: Palopoli
mesh_terms: D000465:Algorithms; D000818:Animals; D006801:Humans; D008954:Models, Biological; D011506:Proteins / Q000378:metabolism; D049490:Systems Biology / Q000379:methods*
chemical_list: D011506:Proteins