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An intelligent data-centric approach toward identification of conserved motifs in protein sequences

Published:02 August 2010Publication History

ABSTRACT

The continued integration of the computational and biological sciences has revolutionized genomic and proteomic studies. However, efficient collaboration between these fields requires the creation of shared standards. A common problem arises when biological input does not properly fit the expectations of the algorithm, which can result in misinterpretation of the output. This potential confounding of input/output is a drawback especially when regarding motif finding software. Here we propose a method for improving output by selecting input based upon evolutionary distance, domain architecture, and known function. This method improved detection of both known and unknown motifs in two separate case studies. By standardizing input considerations, both biologists and bioinformaticians can better interpret and design the evolving sophistication of bioinformatic software.

References

  1. Hedges SB, J Blair, M Venturi, J Shoe. A molecular timescale of eukaryote evolution and the rise of complex multicellular life. BMC Evolutionary Biology. 2004; 4:2.Google ScholarGoogle Scholar
  2. Kumar S, Filipski A, Swarna V, Walker A, Hedges SB. Placing confidence limits on the molecular age of the human-chimpanzee divergence. Proceedings of the Natural Academy of Sciences. 27 Dec 2005; 102(52):18842--18847.Google ScholarGoogle ScholarCross RefCross Ref
  3. Quest D, K Dempsey, M Shafiullah, D Bastola, and H Ali. MTAP: A Motif Tool Assessment Pipeline for Automated Assessment of De Novo Regulatory Motif Discovery Tool. BMC Bioinformatics. 2008 Aug 12; 9 Suppl 9:S6.Google ScholarGoogle Scholar
  4. Tompa M, N Li, T Bailey, G Church, B DeMoor, E Eskin, A Favorov, M Frith, Y Fu, W Kent, V Makeev, A Mironov, W Noble, G Pavesi, G Pesole, M Regnier, N Simonis, S Sinha, G Thijs, J. van Helden, M Vandenbogaert, Z Weng, C Workman, C Ye, and Z Zhu. Assessing Computational Tools for the Discovery of Transcription Factor Binding Sites. Z Nature Biotechnology. 1 Jan 2005; 23(1):137--144.Google ScholarGoogle Scholar
  5. Zheng, J., et al., Prestin is the motor protein of cochlear outer hair cells. Nature, 2000. 405(6783): p. 149--55.Google ScholarGoogle Scholar
  6. Dorwart, M. R., et al., The solute carrier 26 family of proteins in epithelial ion transport. Physiology (Bethesda), 2008. 23: p. 104--14.Google ScholarGoogle ScholarCross RefCross Ref
  7. Yarov-Yarovoy V, Baker D, Catterall WA. Voltage sensor conformations in the open and closed states in ROSETTA structural models of K(+) channels. Proc Natl Acad Sci USA, 2006 May 9; 103(19):7292--7. Epub 2006 Apr 28.Google ScholarGoogle ScholarCross RefCross Ref
  8. Haitin Y, Yisharel I, Malka E, Shamgar L, Schottelndreier H, Peretz A, Paas Y, Attali B. S1 constraints in the voltage sensor domain of Kv7.1 K+ channels. PLoS One. 2008 Apr 9; 3(4):e1935.Google ScholarGoogle Scholar
  9. Heginbotham K, Lu Z, Abramson T, MacKinnon R. Mutations in the K+ channel signature sequence. Biophys J. 1994 Apr; 66(4):1061--7.Google ScholarGoogle Scholar
  10. Crooks GE, Hon G, Chandonia JM, Brenner SE WebLogo: A sequence logo generator, Genome Res, 14:1188--1190, (2004)Google ScholarGoogle ScholarCross RefCross Ref
  1. An intelligent data-centric approach toward identification of conserved motifs in protein sequences

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    • Published in

      cover image ACM Conferences
      BCB '10: Proceedings of the First ACM International Conference on Bioinformatics and Computational Biology
      August 2010
      705 pages
      ISBN:9781450304382
      DOI:10.1145/1854776

      Copyright © 2010 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 2 August 2010

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