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10.15252/msb.20167238 http://scihub22266oqcxt.onion/10.15252/msb.20167238 C5327724!5327724!28167566     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Mol+Syst+Biol 2017 ; 13 (2): ä Nephropedia Template TP {{tp|p=28167566|t=2017. Transcription factor family?specific DNA shape readout revealed by quantitative specificity models |pdf=|usr=}}{{28167566}} gab.com Text Transcription factor family specific DNA shape readout revealed by quantitative specificity models JO: Mol Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=28167566 #FOAvip Transcription factors (TFs) achieve DNA?binding specificity through contacts with functional groups of bases (base readout) and readout of structural properties of the double helix (shape readout). Currently, it remains unclear whether DNA shape readout is utilized by only a few selected TF families, or whether this mechanism is used extensively by most TF families. We resequenced data from previously published HT?SELEX experiments, the most extensive mammalian TF?DNA binding data available to date. Using these data, we demonstrated the contributions of DNA shape readout across diverse TF families and its importance in core motif?flanking regions. Statistical machine?learning models combined with feature?selection techniques helped to reveal the nucleotide position?dependent DNA shape readout in TF?binding sites and the TF family?specific position dependence. Based on these results, we proposed novel DNA shape logos to visualize the DNA shape preferences of TFs. Overall, this work suggests a way of obtaining mechanistic insights into TF?DNA binding without relying on experimentally solved all?atom structures. Twit Text FOAVip Transcription factor family specific DNA shape readout revealed by quantitative specificity models ????Mol Syst Biol http://www.kidney.de/pget.php?&tw=1&pmid=28167566 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28167566 #FOAvip English Wikipedia <ref>{{Cite pmid|28167566}}</ref> Transcription factor family?specific DNA shape readout revealed by quantitative specificity models #MMPMID28167566 Yang L; Orenstein Y; Jolma A; Yin Y; Taipale J; Shamir R; Rohs R Mol Syst Biol 2017[Feb]; 13 (2): ä PMID28167566show ga Transcription factors (TFs) achieve DNA?binding specificity through contacts with functional groups of bases (base readout) and readout of structural properties of the double helix (shape readout). Currently, it remains unclear whether DNA shape readout is utilized by only a few selected TF families, or whether this mechanism is used extensively by most TF families. We resequenced data from previously published HT?SELEX experiments, the most extensive mammalian TF?DNA binding data available to date. Using these data, we demonstrated the contributions of DNA shape readout across diverse TF families and its importance in core motif?flanking regions. Statistical machine?learning models combined with feature?selection techniques helped to reveal the nucleotide position?dependent DNA shape readout in TF?binding sites and the TF family?specific position dependence. Based on these results, we proposed novel DNA shape logos to visualize the DNA shape preferences of TFs. Overall, this work suggests a way of obtaining mechanistic insights into TF?DNA binding without relying on experimentally solved all?atom structures. äTranscription factor family?specific DNA shape readout revealed by qua(epmc).pdf DeepDyve Pubget Overpricing