DASS: efficient discovery and p-value calculation of substructures in unordered data.

Jens Hollunder; Maik Friedel; Andreas Beyer; Christopher T Workman; Thomas Wilhelm

doi:10.1093/bioinformatics/btl511

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DASS: efficient discovery and p-value calculation of substructures in unordered data.

Jens Hollunder·Maik Friedel·Andreas Beyer·Christopher T Workman·Thomas Wilhelm

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Abstract

MOTIVATION: Pattern identification in biological sequence data is one of the main objectives of bioinformatics research. However, few methods are available for detecting patterns (substructures) in unordered datasets. Data mining algorithms mainly developed outside the realm of bioinformatics have been adapted for that purpose, but typically do not determine the statistical significance of the identified patterns. Moreover, these algorithms do not exploit the often modular structure of biological data. RESULTS: We present the algorithm DASS (Discovery of All Significant Substructures) that first identifies all substructures in unordered data (DASS(Sub)) in a manner that is especially efficient for modular data. In addition, DASS calculates the statistical significance of the identified substructures, for sets with at most one element of each type (DASS(P(set))), or for sets with multiple occurrence of elements (DASS(P(mset))). The power and versatility of DASS is demonstrated by four examples: combinations of protein domains in multi-domain proteins, combinations of proteins in protein complexes (protein subcomplexes), combinations of transcription factor target sites in promoter regions and evolutionarily conserved protein interaction subnetworks. AVAILABILITY: The program code and additional data are available at http://www.fli-leibniz.de/tsb/DASS

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Algorithms Escherichia coli Proteins Gene Expression Profiling Models, Genetic Models, Statistical Pattern Recognition, Automated Protein Structure, Tertiary Saccharomyces cerevisiae Proteins Sequence Alignment Sequence Analysis Transcription Factors Journal Article Research Support, Non-U.S. Gov't

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Jens Hollunder, Maik Friedel, Andreas Beyer, Christopher T Workman, Thomas Wilhelm. 2006-10-10. DASS: efficient discovery and p-value calculation of substructures in unordered data.. https://doi.org/10.1093/bioinformatics%2Fbtl511

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