Local graph alignment and motif search in biological networks. Export

@article{citeulike:96165, abstract = {Interaction networks are of central importance in postgenomic molecular biology, with increasing amounts of data becoming available by high-throughput methods. Examples are gene regulatory networks or protein interaction maps. The main challenge in the analysis of these data is to read off biological functions from the topology of the network. Topological motifs, i.e., patterns occurring repeatedly at different positions in the network, have recently been identified as basic modules of molecular information processing. In this article, we discuss motifs derived from families of mutually similar but not necessarily identical patterns. We establish a statistical model for the occurrence of such motifs, from which we derive a scoring function for their statistical significance. Based on this scoring function, we develop a search algorithm for topological motifs called graph alignment, a procedure with some analogies to sequence alignment. The algorithm is applied to the gene regulation network of Escherichia coli.}, address = {Institut f\"{u}r Theoretische Physik, Universit\"{a}t zu K\"{o}ln, Z\"{u}lpicherstrasse 77, 50937 Cologne, Germany. berg@thp.uni-koeln.de}, author = {Berg, Johannes and L\"{a}ssig, Michael}, citeulike-article-id = {96165}, citeulike-linkout-0 = {http://dx.doi.org/10.1073/pnas.0305199101}, citeulike-linkout-1 = {http://www.pnas.org/content/101/41/14689.abstract}, citeulike-linkout-2 = {http://www.pnas.org/content/101/41/14689.full.pdf}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/15448202}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=15448202}, day = {12}, doi = {10.1073/pnas.0305199101}, issn = {0027-8424}, journal = {Proceedings of the National Academy of Sciences of the United States of America}, keywords = {graphs, networks}, month = {October}, number = {41}, pages = {14689--14694}, posted-at = {2005-05-12 17:59:32}, priority = {4}, title = {Local graph alignment and motif search in biological networks.}, url = {http://dx.doi.org/10.1073/pnas.0305199101}, volume = {101}, year = {2004} }

TY - JOUR ID - citeulike:96165 L3 - citeulike-article-id:96165 N2 - Interaction networks are of central importance in postgenomic molecular biology, with increasing amounts of data becoming available by high-throughput methods. Examples are gene regulatory networks or protein interaction maps. The main challenge in the analysis of these data is to read off biological functions from the topology of the network. Topological motifs, i.e., patterns occurring repeatedly at different positions in the network, have recently been identified as basic modules of molecular information processing. In this article, we discuss motifs derived from families of mutually similar but not necessarily identical patterns. We establish a statistical model for the occurrence of such motifs, from which we derive a scoring function for their statistical significance. Based on this scoring function, we develop a search algorithm for topological motifs called graph alignment, a procedure with some analogies to sequence alignment. The algorithm is applied to the gene regulation network of Escherichia coli. IS - 41 JF - Proceedings of the National Academy of Sciences of the United States of America SN - 0027-8424 AD - Institut für Theoretische Physik, Universität zu Köln, Zülpicherstrasse 77, 50937 Cologne, Germany. berg@thp.uni-koeln.de EP - 14694 TI - Local graph alignment and motif search in biological networks. VL - 101 SP - 14689 KW - graphs KW - networks AU - Berg, Johannes AU - Lässig, Michael PY - 2004/10/12/ UR - http://dx.doi.org/10.1073/pnas.0305199101 ER -