Self-organizing neural networks to support the discovery of DNA-binding motifs
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
Detection of over-represented motifs corresponding to known TFBSs via motif clustering and matching
Computers & Mathematics with Applications
Parallel Position Weight Matrices algorithms
Parallel Computing
Large scale matching for position weight matrices
CPM'06 Proceedings of the 17th Annual conference on Combinatorial Pattern Matching
Pattern recognition in bioinformatics: an introduction
PRIB'06 Proceedings of the 2006 international conference on Pattern Recognition in Bioinformatics
RCG'06 Proceedings of the RECOMB 2006 international conference on Comparative Genomics
Hi-index | 3.84 |
Motivation: Transcription-factor binding sites (TFBS) in promoter sequences of higher eukaryotes are commonly modeled using position frequency matrices (PFM). The ability to compare PFMs representing binding sites is especially important for de novo sequence motif discovery, where it is desirable to compare putative matrices to one another and to known matrices. Results: We describe a PFM similarity quantification method based on product multinomial distributions, demonstrate its ability to identify PFM similarity and show that it has a better false positive to false negative ratio compared to existing methods. We grouped TFBS frequency matrices from two libraries into matrix families and identified the matrices that are common and unique to these libraries. We identified similarities and differences between the skeletal-muscle-specific and non-muscle-specific frequency matrices for the binding sites of Mef-2, Myf, Sp-1, SRF and TEF of Wasserman and Fickett. We further identified known frequency matrices and matrix families that were strongly similar to the matrices given by Wasserman and Fickett. We provide methodology and tools to compare and query libraries of frequency matrices for TFBSs. Availability: Software is available to use over the Web at http://rulai.cshl.edu/MatCompare Contact: dschones@cshl.edu Supplementary information: Database and clustering statistics, matrix families and representatives are available at http://rulai.cshl.edu/MatCompare/Supplementary