Survey of variation in human transcription factors reveals prevalent DNA binding changes

Survey of variation in human transcription factors reveals prevalent DNA binding changes

Sequencing of exomes and genomes has revealed abundant genetic variation affecting the coding sequences of human transcription factors (TFs), but the consequences of such variation remain largely unexplored. We developed a computational, structure-based approach to evaluate TF variants for their imp...

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Main Authors: Vedenko, A. (Author), Kurland, J. V. (Author), Rogers, J. M. (Author), Gisselbrecht, S. S. (Author), Woodard, J. (Author), Mariani, L. (Author), Kock, K. H. (Author), Inukai, S. (Author), Siggers, T. (Author), Shokri, L. (Author), Gordan, R. (Author), Sahni, N. (Author), Cotsapas, C. (Author), Hao, T. (Author), Yi, S. (Author), Vidal, M. (Author), Hill, D. E. (Author), Barrera, Luis Alberto (Contributor), Rossin, Elizabeth (Contributor), Kellis, Manolis (Contributor), Daly, Mark J. (Author), Bulyk, Martha L. (Author)
Other Authors: Massachusetts Institute of Technology. Institute for Medical Engineering & Science (Contributor), Broad Institute of MIT and Harvard (Contributor), Harvard University- (Contributor), Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Daly, Mark J (Contributor), Bulyk, Martha L (Contributor)
Format: Article
Language:English
Published: American Association for the Advancement of Science (AAAS), 2017-09-01T13:57:35Z.
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