TY - GEN
T1 - Discovering coherent value bicliques in genetic interaction data
AU - Atluri, Gowtham
AU - Bellay, Jeremy
AU - Pandey, Gaurav
AU - Myers, Chad
AU - Kumar, Vipin
N1 - Publisher Copyright:
Copyright © 2010 ACM.
PY - 2010
Y1 - 2010
N2 - Genetic Interaction (GI) data provides a means for exploring the structure and function of pathways in a cell. Coherent value bicliques (submatrices) in GI data represents functionally similar gene modules or protein complexes. However, no systematic approach has been proposed for exhaustively enumerating all coherent value submatrices in such data sets, which is the problem addressed in this paper. Using a monotonic range measure to capture the coherence of values in a submatrix of an input data matrix, we propose a two-step Apriori-based algorithm for discovering all nearly constant value submatrices, referred to as Range Constrained Blocks. By systematic evaluation on an extensive genetic interaction data set, we show that the coherent value submatrices represent groups of genes that are functionally related than the submatrices with diverse values. We also show that our approach can exhaustively find all the submatrices with a range less than a given threshold, while the other competing approaches can not find all such submatrices.
AB - Genetic Interaction (GI) data provides a means for exploring the structure and function of pathways in a cell. Coherent value bicliques (submatrices) in GI data represents functionally similar gene modules or protein complexes. However, no systematic approach has been proposed for exhaustively enumerating all coherent value submatrices in such data sets, which is the problem addressed in this paper. Using a monotonic range measure to capture the coherence of values in a submatrix of an input data matrix, we propose a two-step Apriori-based algorithm for discovering all nearly constant value submatrices, referred to as Range Constrained Blocks. By systematic evaluation on an extensive genetic interaction data set, we show that the coherent value submatrices represent groups of genes that are functionally related than the submatrices with diverse values. We also show that our approach can exhaustively find all the submatrices with a range less than a given threshold, while the other competing approaches can not find all such submatrices.
UR - http://www.scopus.com/inward/record.url?scp=84908308171&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84908308171
T3 - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
SP - 125
EP - 132
BT - Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
PB - Association for Computing Machinery
T2 - 9th International Workshop on Data Mining in Bioinformatics, BIOKDD 2010, Held in Conjunction with 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Y2 - 25 July 2010 through 28 July 2010
ER -