image University of Washington Computer Science & Engineering
 Software from the Computational Molecular Biology Group
  CSE Home   About Us    Search    Contact Info 

 COSMO
 Dapple
 FootPrinter
 MicroFootPrinter
 PhyME
 Projection
 StatSigMA
 YMF
    FootPrinter2.1 Web Server: A program for phylogenetic footprinting
Download FootPrinter2.1
Sample output

Phylogenetic footprinting is a method that identifies putative regulatory elements in DNA sequences. It identifies regions of DNA that are unusually well conserved across a set of orthologous sequences.

If you use this software for your publications, please read and cite:

  1. Blanchette, M. and Tompa, M. FootPrinter: a program designed for phylogenetic footprinting. Nucleic Acids Research, vol. 31, no. 13, 2003, 3840-3842.
  2. Blanchette, M. and Tompa, M. Discovery of Regulatory Elements by a Computational Method for Phylogenetic Footprinting. Genome Research, vol. 12, no. 5, May 2002, 739-748 and
  3. Blanchette, M., Schwikowski, B., and Tompa, M. Algorithms for Phylogenetic Footprinting. Journal of Computational Biology, vol. 9, no. 2, 2002, 211-223.
MicroFootPrinter: A microbial front end for FootPrinter

MicroFootPrinter is a front end to the FootPrinter phylogenetic footprinting program, but with specific focus on prokaryotic genomes. You supply a prokaryotic species and gene of interest. MicroFootPrinter will then find related prokaryotes each containing a homologous gene, and run FootPrinter to identify motifs in the regulatory region of your chosen gene that are well conserved across these homologous genes.

If you use this software for your publications, please read and cite:

Neph, S. and Tompa, M., MicroFootPrinter: a Tool for Phylogenetic Footprinting in Prokaryotic Genomes. Nucleic Acids Research, vol. 34, July 2006, W366-W368.

YMF and FindExplanators Web Server: An enumerative motif discovery program.
Download YMF and FindExplanators

YMF identifies motifs (made of IUPAC symbols) that occur unsually often in a given set of sequences. FindExplanators extracts from that set of motifs a smaller set of independent motifs.

If you use this software for your publications, please read and cite:

  1. Sinha, S. and Tompa, M., YMF: a Program for Discovery of Novel Transcription Factor Binding Sites by Statistical Overrepresentation. Nucleic Acids Research, vol. 31, no. 13, July 2003, 3586-3588.
  2. Sinha, S. and Tompa, M. Discovery of Novel Transcription Factor Binding Sites by Statistical Overrepresentation. Nucleic Acids Research, vol. 30, no. 24, December 2002, 5549-5560.
  3. Sinha, S. and Tompa, M. A Statistical Method for Finding Transcription Factor Binding Sites, Eighth International Conference on Intelligent Systems for Molecular Biology, San Diego, CA, August 2000, 344-354.
  4. Blanchette, M. and Sinha, S. Separating real motifs from their artifacts. Bioinformatics, vol. 17, 2001, S30-S38.
StatSigMA: Statistical Significance of Multiple Alignments

StatSigMA computes the statistical significance of multiple sequence alignments (of either nucleotide or amino acid sequences), much as BLAST's E-values provide statistical significance for pairwise alignments.

If you use this software for your publications, please read and cite:

Prakash, A. and Tompa, M., Statistics of local multiple alignments. 13th Annual International Conference on Intelligent Systems for Molecular Biology, Detroit, MI, June 2005. Bioinformatics, vol. 21, June 2005, i344 - i350.

PhyME: Motif discovery in data sets that include both intraspecies overrepresentation and interspecies conservation

PhyME discovers motifs by integrating two important aspects of the motif's significance, overrepresentation and interspecies conservation, into one probabilistic score. The algorithm is based on multiple alignment and expectation-maximization.

If you use this software for your publications, please read and cite:

Sinha, S., Blanchette, M., and Tompa, M. PhyME: A Probabilistic Algorithm for Finding Motifs in Sets of Orthologous Sequences. BMC Bioinformatics, vol. 5, 2004, 170.

COSMO: Binding sites in coding regions

COSMO is a program that detects putative binding sites in coding regions.Given a set of orthologous mRNA sequences, it identifies regions whose conservation cannot be explained solely by the selective pressure on the protein encoded.

If you use this software for your publications, please read and cite:

Blanchette, M. A comparative analysis method for detecting binding sites in coding regions. In Proceedings of the Seventh Annual International Conference on Computational Molecular Biology (RECOMB03), Berlin, 2003.

Projection: A motif discovery program based on random projections

If you use this software for your publications, please read and cite:

  1. Buhler, J. and Tompa, M. Finding Motifs Using Random Projections. Journal of Computational Biology, vol. 9, no. 2, 2002, 225-242.
  2. Buhler, J. Provably sensitive indexing strategies for biosequence similarity search. In Proceedings of the Sixth Annual International Conference on Computational Molecular Biology (RECOMB02) 90-99, Washington, D.C., 2002.

Dapple: Image analysis software for DNA microarrays

Dapple is a program for quantitating spots on a two-color DNA microarray image. Given a pair of images from a comparative hybridization, Dapple finds the individual spots on the image, evaluates their qualities, and quantifies their total fluorescent intensities.

If you use this software for your publications, please read and cite:

Buhler, J., Ideker, T., and Haynor, D. Dapple: Improved Techniques for Finding Spots on DNA Microarrays. UW CSE Technical Report 2000-08-05.
 

CSE logo Computer Science & Engineering
University of Washington
Box 352350
Seattle, WA  98195-2350
(206) 543-1695 voice, (206) 543-2969 FAX
[comments to bio-webmaster]