publication . Preprint . Conference object . Other literature type . 2017

MotifMark: Finding Regulatory Motifs in DNA Sequences

Hassanzadeh, Hamid Reza; Kolhe, Pushkar; Isbell, Charles L.; Wang, May D.;
Open Access
  • Published: 05 May 2017
  • Publisher: Cold Spring Harbor Laboratory
<jats:title>Abstract</jats:title><jats:p>The interaction between proteins and DNA is a key driving force in a significant number of biological processes such as transcriptional regulation, repair, recombination, splicing, and DNA modification. The identification of DNA-binding sites and the specificity of target proteins in binding to these regions are two important steps in understanding the mechanisms of these biological activities. A number of high-throughput technologies have recently emerged that try to quantify the affinity between proteins and DNA motifs. Despite their success, these technologies have their own limitations and fall short in precise charac...
free text keywords: Haystack, Binding site, DNA sequencing, Computational biology, RNA splicing, Genetics, DNA, chemistry.chemical_compound, chemistry, Plasma protein binding, Transcription factor, Biology, DNA microarray, Computer vision, Artificial intelligence, business.industry, business, Computer science, Quantitative Biology - Quantitative Methods, Computer Science - Learning, Quantitative Biology - Genomics, Article
Related Organizations
Funded by
NIH| Atlanta Clinical and Translational Science Institute (ACTSI) Renewal
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5UL1TR000454-07
NIH| Contrast-Enhanced and Image-Guided Surgery of Lung Cancer
  • Funder: National Institutes of Health (NIH)
  • Project Code: 5R01CA163256-02

Münsterkötter, K. Nenova, et al., "PEDANT covers all complete RefSeq genomes," Nucleic acids research, vol. 37, pp. D408- D411, 2009.

S. Mukherjee, M. F. Berger, G. Jona, X. S. Wang, D. Muzzey, M. Snyder, et al., "Rapid analysis of the DNA-binding specificities of transcription factors with DNA microarrays," Nature genetics, vol. 36, pp. 1331-1339, 2004.

Riley, et al., "Evaluation of methods for modeling transcription factor sequence specificity," Nature biotechnology, vol. 31, pp.

N. Jayaram, D. Usvyat, and A. C. Martin, "Evaluating tools for transcription factor binding site prediction," BMC bioinformatics, pp. 1-12, 2016. [OpenAIRE]

X. Chen, T. R. Hughes, and Q. Morris, "RankMotif++: a motifsearch algorithm that accounts for relative ranks of K-mers in binding transcription factors," Bioinformatics, vol. 23, pp. i72- i79, 2007.

K.-C. Wong, T.-M. Chan, C. Peng, Y. Li, and Z. Zhang, "DNA motif elucidation using belief propagation," Nucleic Acids Research, vol. 41, p. e153, 2013.

H. R. Hassanzadeh and M. D. Wang, "DeeperBind: Enhancing Prediction of Sequence Specificities of DNA Binding Proteins," 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 178-183, 2016.

Z. Wu and R. Leahy, "An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation," IEEE transactions on pattern analysis and machine intelligence, vol. 15, pp. 1101-1113, 1993.

J. Shi and J. Malik, "Normalized cuts and image segmentation," IEEE Transactions on pattern analysis and machine intelligence, vol. 22, pp. 888-905, 2000.

Powered by OpenAIRE Research Graph
Any information missing or wrong?Report an Issue