T L Bailey

Summary

Affiliation: University of California
Country: USA

Publications

  1. ncbi request reprint Score distributions for simultaneous matching to multiple motifs
    T L Bailey
    San Diego Supercomputer Center, California 92186 9784, USA
    J Comput Biol 4:45-59. 1997
  2. ncbi request reprint Methods and statistics for combining motif match scores
    T L Bailey
    San Diego Supercomputer Center, California 92186 9784, USA
    J Comput Biol 5:211-21. 1998
  3. ncbi request reprint Estimating and evaluating the statistics of gapped local-alignment scores
    Timothy L Bailey
    ACMC, Mathematics Department, The University of Queensland, Brisbane, Queensland, 4072 Australia
    J Comput Biol 9:575-93. 2002
  4. ncbi request reprint The megaprior heuristic for discovering protein sequence patterns
    T L Bailey
    San Diego Supercomputer Center, San Diego, California 92186 9784, USA
    Proc Int Conf Intell Syst Mol Biol 4:15-24. 1996
  5. pmc Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data
    Robert C McLeay
    Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
    BMC Bioinformatics 11:165. 2010
  6. pmc Discriminative motif discovery in DNA and protein sequences using the DEME algorithm
    Emma Redhead
    Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, 4072 Australia
    BMC Bioinformatics 8:385. 2007
  7. pmc The value of position-specific priors in motif discovery using MEME
    Timothy L Bailey
    Institute for Molecular Bioscience, The University of Queensland, Brisbane 4072, Queensland, Australia
    BMC Bioinformatics 11:179. 2010
  8. pmc MEME SUITE: tools for motif discovery and searching
    Timothy L Bailey
    Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
    Nucleic Acids Res 37:W202-8. 2009
  9. pmc Optimizing static thermodynamic models of transcriptional regulation
    Denis C Bauer
    Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
    Bioinformatics 25:1640-6. 2009
  10. doi request reprint Discovering sequence motifs
    Timothy L Bailey
    ARC Centre of Excellence in Bioinformatics, and Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
    Methods Mol Biol 452:231-51. 2008

Collaborators

Detail Information

Publications27

  1. ncbi request reprint Score distributions for simultaneous matching to multiple motifs
    T L Bailey
    San Diego Supercomputer Center, California 92186 9784, USA
    J Comput Biol 4:45-59. 1997
    ....
  2. ncbi request reprint Methods and statistics for combining motif match scores
    T L Bailey
    San Diego Supercomputer Center, California 92186 9784, USA
    J Comput Biol 5:211-21. 1998
    ..The MAST sequence homology search algorithm utilizing the product of p-values scoring method is available for interactive use and downloading at URL http:/(/)www.sdsc.edu/MEME...
  3. ncbi request reprint Estimating and evaluating the statistics of gapped local-alignment scores
    Timothy L Bailey
    ACMC, Mathematics Department, The University of Queensland, Brisbane, Queensland, 4072 Australia
    J Comput Biol 9:575-93. 2002
    ..We explain this paradox and argue that statistical accuracy, not classification accuracy, should be the primary criterion in comparisons of similarity search methods that return p-values that adjust for target sequence length...
  4. ncbi request reprint The megaprior heuristic for discovering protein sequence patterns
    T L Bailey
    San Diego Supercomputer Center, San Diego, California 92186 9784, USA
    Proc Int Conf Intell Syst Mol Biol 4:15-24. 1996
    ....
  5. pmc Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data
    Robert C McLeay
    Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland 4072, Australia
    BMC Bioinformatics 11:165. 2010
    ..In this paper, we explore ways to make MEA applicable in more settings, and evaluate the efficacy of a number of MEA approaches...
  6. pmc Discriminative motif discovery in DNA and protein sequences using the DEME algorithm
    Emma Redhead
    Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, 4072 Australia
    BMC Bioinformatics 8:385. 2007
    ....
  7. pmc The value of position-specific priors in motif discovery using MEME
    Timothy L Bailey
    Institute for Molecular Bioscience, The University of Queensland, Brisbane 4072, Queensland, Australia
    BMC Bioinformatics 11:179. 2010
    ....
  8. pmc MEME SUITE: tools for motif discovery and searching
    Timothy L Bailey
    Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
    Nucleic Acids Res 37:W202-8. 2009
    ..All of the motif-based tools are now implemented as web services via Opal. Source code, binaries and a web server are freely available for noncommercial use at http://meme.nbcr.net...
  9. pmc Optimizing static thermodynamic models of transcriptional regulation
    Denis C Bauer
    Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
    Bioinformatics 25:1640-6. 2009
    ..In particular, we see no advantage to using the more sophisticated 'LAM' cooling schedule. Overall, a good approximate solution is achievable in minutes using SA with a simple cooling schedule...
  10. doi request reprint Discovering sequence motifs
    Timothy L Bailey
    ARC Centre of Excellence in Bioinformatics, and Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
    Methods Mol Biol 452:231-51. 2008
    ..A discussion of some limitations of motif discovery concludes the chapter...
  11. pmc Associating transcription factor-binding site motifs with target GO terms and target genes
    Mikael Boden
    Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
    Nucleic Acids Res 36:4108-17. 2008
    ..Results on human reference sets are similarly encouraging. Validation of our target gene prediction method shows that its accuracy exceeds that of simple motif scanning...
  12. pmc Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures
    Mikael Boden
    School of Information Technology and Electrical Engineering, The University of Queensland, QLD 4072, St Lucia, Australia
    BMC Bioinformatics 7:68. 2006
    ..e. assigning probabilities to the conformational states of a residue. We train our methods using data derived from high-quality NMR models...
  13. ncbi request reprint Searching for statistically significant regulatory modules
    Timothy L Bailey
    Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
    Bioinformatics 19:ii16-25. 2003
    ..True binding sites may be identified by their tendency to occur in clusters, sometimes known as regulatory modules...
  14. doi request reprint Discovering novel sequence motifs with MEME
    Timothy L Bailey
    University of Queensland, Brisbane, Australia
    Curr Protoc Bioinformatics . 2002
    ..MEME also produces block diagrams showing where all of the discovered motifs occur in the training set sequences. MEME's hypertext (HTML) output also contains buttons that allow for the convenient use of the motifs in other searches...
  15. pmc STREAM: Static Thermodynamic REgulAtory Model of transcription
    Denis C Bauer
    Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia
    Bioinformatics 24:2544-5. 2008
    ..g. different tissues, knockout/additional TFs or mutated/missing TFBSs)...
  16. ncbi request reprint Discrimination of non-protein-coding transcripts from protein-coding mRNA
    Martin C Frith
    Genome Exploration Research Group Genome Network Project Core Group, RIKEN Genomic Sciences Center GSC, RIKEN Yokohama Institute, Kanagawa, Japan
    RNA Biol 3:40-8. 2006
    ..Conversely and surprisingly, our analyses also provide evidence that as much as approximately 10% of entries in the manually curated protein database Swiss-Prot are erroneous translations of actually non-coding transcripts...
  17. ncbi request reprint Discovering sequence motifs
    Timothy L Bailey
    IMB University of Queensland
    Methods Mol Biol 395:271-92. 2007
    ..A discussion of some limitations of motif discovery concludes the chapter...
  18. ncbi request reprint Identifying sequence regions undergoing conformational change via predicted continuum secondary structure
    Mikael Boden
    School of Information Technology and Electrical Engineering, QLD 4072, The University of Queensland Australia
    Bioinformatics 22:1809-14. 2006
    ....
  19. pmc Quantifying similarity between motifs
    Shobhit Gupta
    Department of Genome Sciences, University of Washington, 1705 NE Pacific Street, Box 355065, Seattle, WA 98195, USA
    Genome Biol 8:R24. 2007
    ..Experimental simulations demonstrate the accuracy of Tomtom's E values and its effectiveness in finding similar motifs...
  20. ncbi request reprint Prediction of protein B-factor profiles
    Zheng Yuan
    Institute for Molecular Bioscience and ARC Centre in Bioinformatics, The University of Queensland, St Lucia, Australia
    Proteins 58:905-12. 2005
    ..flexible). For almost all predicted B-factor thresholds, prediction accuracies (percent of correctly predicted residues) are greater than 70%. These results exceed the best results of other sequence-based prediction methods...
  21. pmc GONOME: measuring correlations between GO terms and genomic positions
    Stefan M Stanley
    Institute for Molecular Bioscience, University of Queensland, Brisbane 4072, Australia
    BMC Bioinformatics 7:94. 2006
    ..However, due to the varying length of genes and intergenic regions, that approach is inappropriate for deciding if any GO terms are correlated with a set of genomic positions...
  22. pmc Pseudo-messenger RNA: phantoms of the transcriptome
    Martin C Frith
    Genome Exploration Research Group Genome Network Project Core Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Yokohama, Japan
    PLoS Genet 2:e23. 2006
    ..Many of these transcripts do not correspond cleanly to any identifiable object in the genome, implying fundamental limits to the goal of annotating all functional elements at the genome sequence level...
  23. pmc The abundance of short proteins in the mammalian proteome
    Martin C Frith
    Genome Exploration Research Group Genome Network Project Core Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute, Yokohama, Japan
    PLoS Genet 2:e52. 2006
    ..Translation assays confirm that some of these novel proteins can be translated and localised to the secretory pathway...
  24. ncbi request reprint Assessing computational tools for the discovery of transcription factor binding sites
    Martin Tompa
    Department of Computer Science and Engineering, Box 352350, University of Washington, Seattle, Washington 98195 2350, USA
    Nat Biotechnol 23:137-44. 2005
    ..The purpose of the current assessment is twofold: to provide some guidance to users regarding the accuracy of currently available tools in various settings, and to provide a benchmark of data sets for assessing future tools...
  25. pmc MEME: discovering and analyzing DNA and protein sequence motifs
    Timothy L Bailey
    Institute of Molecular Bioscience, The University of Queensland, St Lucia, QLD 4072, Australia
    Nucleic Acids Res 34:W369-73. 2006
    ..This article describes the freely accessible web server and its architecture, and discusses ways to use MEME effectively to find new sequence patterns in biological sequences and analyze their significance...
  26. pmc Studying the functional conservation of cis-regulatory modules and their transcriptional output
    Denis C Bauer
    Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072 Australia
    BMC Bioinformatics 9:220. 2008
    ....
  27. pmc Discovering sequence motifs with arbitrary insertions and deletions
    Martin C Frith
    Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology AIST, Tokyo, Japan
    PLoS Comput Biol 4:e1000071. 2008
    ..It may be equally useful for arbitrarily gapped motifs in DNA and RNA, although fewer examples of such motifs are known at present. GLAM2 is public domain software, available for download at http://bioinformatics.org.au/glam2...