are complemented by microarray data, RNAi knockout experimental data, interaction data, gene regulatory infor- mation and functional categorization using the GO categories. Proteins, besides containing complete annota- tions, are enhanced by the addition of SwissProt/TrEMBL cross-references, physical structure details and properties and orthology/paralogy information. Finally, groups of all types of biots and biot information are linked together by patterns found by CDM, as described in the CDM section. Data sources Genome annotation data (chromosomes, genes, proteins, sequences, transcripts) for C. elegans are retrieved from Wormbase (2). Attention has been paid to retaining all transcripts and their respective constituting coding sequences for each gene. These transcripts serve as a link to gene expression data and RNAi transcript information. Gene orthology and paralogy data have also been taken from Wormbase. Protein sequences and annotations have been obtained from Wormbase, while their physical properties and Protein Data Bank [PDB; (11)] homologs have been obtained from the Structural Genomics of C. elegans [SGCE; (12)] project. Protein interaction data and gene regulatory information have been obtained from BioGRID (13). Internal mappings from BioGRID IDs to Wormbase IDs have been generated. Genome-wide gene expression data for 496 C. elegans microarray experiments have been collected from Stanford Microarray Database [SMD; (14)]. Expression values have been related to the genes through gene transcripts. The RNAi component of CMGSDB is one of the chief characteristics that separates CMGSDB from other C. elegans resources. The RNAi experiments obtained from Wormbase have been supplemented by RNAi experiments retrieved from Phenobank (15), PhenomicDB (16) and RNAi phenome database (17). The same has been done for RNAi phenotypes. All RNAi phenotypes, thus obtained, have been organized into a hierarchical structure, with body, cell, development, lethal and sterile and miscellaneous as the top phenotypic categories. While Phenobank’s experiments test all C. elegans genes for their role in the ﬁrst two rounds of mitotic cell division, RNAi phenome database’s experiments are aimed at evaluating the eﬀects of RNAi on genes whose knock down causes embryonic lethality. PhenomicDB is a multi-organism phenotype–genotype database including human, mouse, fruit ﬂy, C. elegans and other model organisms. Apart from these web-based RNAi data sources, there are a number of genome-wide RNAi screens in literature that are undocumented in these web-based sources but have been included in CMGSDB (18–36). Database schema The key components of CMGSDB are illustrated in Figure 2. Biots are contained in light green boxes, which are represented by one or more relations in CMGSDB. Nucleic Acids Research, 2008, Vol. 36, Database issue D71 Figure 2. Data integration and analysis in CMGSDB. Blue arrows represent relationships in CMGSDB. Plain black arrows represent data ﬂow. Applying CDM to CMGSDB We applied CDM to CMGSDB as follows. There are a variety of biclustering algorithms that can be applied for mining relationships (37). For the purpose of this study, we utilized CHARM (38) to mine biclusters in binary relationships. For gene expression data, we utilized SAMBA (5) to mine biclusters. Given a binary 0–1 matrix, the CHARM algorithm identiﬁes sets of rows that show the same bit (0/1) patterns across all columns. The row set is grown to be maximal in size and, together with the columns for which the rows have a ‘1’, deﬁnes the bicluster. CHARM identiﬁes