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10.1073/pnas.1715888115 http://scihub22266oqcxt.onion/10.1073/pnas.1715888115 C5910820!5910820!29588420     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\29588420.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Proc+Natl+Acad+Sci+U+S+A 2018 ; 115 (16): E3702-11 Nephropedia Template TP {{tp|p=29588420|t=2018. Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding |pdf=|usr=}}{{29588420}} gab.com Text Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=29588420 #FOAvip Transcription factors (TFs) are key proteins that bind DNA targets to coordinate gene expression in cells. Understanding how TFs recognize their DNA targets is essential for predicting how variations in regulatory sequence disrupt transcription to cause disease. Here, we develop a high-throughput assay and analysis pipeline capable of measuring binding energies for over one million sequences with high resolution and apply it toward understanding how nucleotides flanking DNA targets affect binding energies for two model yeast TFs. Through systematic comparisons between models trained on these data, we establish that considering dinucleotide (DN) interactions is sufficient to accurately predict binding and further show that sites used by TFs in vivo are both energetically and mutationally distant from the highest affinity sequence. Twit Text FOAVip Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=29588420 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29588420 #FOAvip English Wikipedia <ref>{{Cite pmid|29588420}}</ref> Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding #MMPMID29588420 Le DD; Shimko TC; Aditham AK; Keys AM; Longwell SA; Orenstein Y; Fordyce PM Proc Natl Acad Sci U S A 2018[Apr]; 115 (16): E3702-11 PMID29588420show ga Transcription factors (TFs) are key proteins that bind DNA targets to coordinate gene expression in cells. Understanding how TFs recognize their DNA targets is essential for predicting how variations in regulatory sequence disrupt transcription to cause disease. Here, we develop a high-throughput assay and analysis pipeline capable of measuring binding energies for over one million sequences with high resolution and apply it toward understanding how nucleotides flanking DNA targets affect binding energies for two model yeast TFs. Through systematic comparisons between models trained on these data, we establish that considering dinucleotide (DN) interactions is sufficient to accurately predict binding and further show that sites used by TFs in vivo are both energetically and mutationally distant from the highest affinity sequence. äComprehensive, high-resolution binding energy landscapes reveal contex(epmc).pdf DeepDyve Pubget Overpricing