A Knowledge-Based Clustering Algorithm Driven by Gene Ontology Export

@article{Cheng2004, abstract = {We have developed an algorithm for inferring the degree of similarity between genes by using the graph-based structure of Gene Ontology (GO). We applied this knowledge-based similarity metric to a clique-finding algorithm for detecting sets of related genes with biological classifications. We also combined it with an expression-based distance metric to produce a co-cluster analysis, which accentuates genes with both similar expression profiles and similar biological characteristics and identifies gene clusters that are more stable and biologically meaningful. These algorithms are demonstrated in the analysis of MPRO cell differentiation time series experiments.}, author = {Cheng, Jill and Cline, Melissa and Martin, John and Finkelstein, David and Awad, Tarif and Kulp, David and Siani-Rose, Michael A.}, citeulike-article-id = {5818237}, citeulike-linkout-0 = {http://dx.doi.org/10.1081/BIP-200025659}, doi = {10.1081/BIP-200025659}, journal = {Journal of Biopharmaceutical Statistics}, keywords = {gene-ontology, semantic-similarity}, number = {3}, pages = {687--700}, posted-at = {2009-09-22 04:56:28}, priority = {2}, publisher = {Taylor \& Francis}, title = {A Knowledge-Based Clustering Algorithm Driven by Gene Ontology}, url = {http://dx.doi.org/10.1081/BIP-200025659}, volume = {14}, year = {2004} }

TY - JOUR ID - Cheng2004 L3 - citeulike-article-id:5818237 N2 - We have developed an algorithm for inferring the degree of similarity between genes by using the graph-based structure of Gene Ontology (GO). We applied this knowledge-based similarity metric to a clique-finding algorithm for detecting sets of related genes with biological classifications. We also combined it with an expression-based distance metric to produce a co-cluster analysis, which accentuates genes with both similar expression profiles and similar biological characteristics and identifies gene clusters that are more stable and biologically meaningful. These algorithms are demonstrated in the analysis of MPRO cell differentiation time series experiments. IS - 3 JF - Journal of Biopharmaceutical Statistics EP - 700 TI - A Knowledge-Based Clustering Algorithm Driven by Gene Ontology PB - Taylor & Francis VL - 14 SP - 687 KW - gene-ontology KW - semantic-similarity AU - Cheng, Jill AU - Cline, Melissa AU - Martin, John AU - Finkelstein, David AU - Awad, Tarif AU - Kulp, David AU - Siani-Rose, Michael PY - 2004/// UR - http://dx.doi.org/10.1081/BIP-200025659 ER -