Self-organizing neural networks to support the discovery of DNA-binding motifs
Neural Networks - 2006 Special issue: Advances in self-organizing maps--WSOM'05
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A Method to Find Sequentially Separated Motifs in Biological Sequences (SSMBS)
PRIB '08 Proceedings of the Third IAPR International Conference on Pattern Recognition in Bioinformatics
It's not junk!: the search for functional elements in noncoding DNA
ACM SIGEVOlution
Establishing a statistic model for recognition of steroid hormone response elements
Computational Biology and Chemistry
ML-Consensus: a general consensus model for variable-length transcription factor binding sites
EvoBIO'11 Proceedings of the 9th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Computational Biology and Chemistry
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Motivation: Promoter analysis is an essential step on the way to identify regulatory networks. A prerequisite for successful promoter analysis is the prediction of potential transcription factor binding sites (TFBS) with reasonable accuracy. The next steps in promoter analysis can be tackled only with reliable predictions, e.g. finding phylogenetically conserved patterns or identifying higher order combinations of sites in promoters of co-regulated genes. Results: We present a new version of the program MatInspector that identifies TFBS in nucleotide sequences using a large library of weight matrices. By introducing a matrix family concept, optimized thresholds, and comparative analysis, the enhanced program produces concise results avoiding redundant and false-positive matches. We describe a number of programs based on MatInspector allowing in-depth promoter analysis (DiAlignTF, FrameWorker) and targeted design of regulatory sequences (SequenceShaper). Availability: MatInspector and the other programs described here can be used online at http://www.genomatix.de/matinspector.html. Access is free after registration within certain limitations (e.g. the number of analysis per month is currently limited to 20 analyses of arbitrary sequences). Contact: cartharius@genomatix.de Supplementary information: http://www.genomatix.de/matinspector.html