Clustering gene expression patterns
RECOMB '99 Proceedings of the third annual international conference on Computational molecular biology
An algorithm for clustering cDNAs for gene expression analysis
RECOMB '99 Proceedings of the third annual international conference on Computational molecular biology
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Biclustering of Expression Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Complexity Study on Two Clustering Problems
ISAAC '01 Proceedings of the 12th International Symposium on Algorithms and Computation
Finding biclusters by random projections
Theoretical Computer Science
Inapproximability of maximum weighted edge biclique and its applications
TAMC'08 Proceedings of the 5th international conference on Theory and applications of models of computation
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A novel clustering approach is introduced to overcome data missing and inconsistency of gene expression levels under different conditions in the stage of clustering. It is based on the so-called smooth score, which is defined for measuring the deviation of the expression level of a gene and the average expression level of all the genes involved under a condition. We present an efficient greedy algorithm for finding clusters with smooth score below a threshold after studying its computational complexity. The algorithm was tested intensively on random matrixes and a yeast data. It was shown to perform well in finding co-regulation patterns in a test with the yeast data.