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10.1038/nmeth.4560 http://scihub22266oqcxt.onion/10.1038/nmeth.4560 C6029251!6029251 !29334377     free     free     free Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 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\29334377 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Nat+Methods 2018 ; 15 (2 ): 119-122 Nephropedia Template TP {{tp|p=29334377 |t=2018. Detecting hierarchical genome folding with network modularity |pdf=|usr=}}{{29334377 }} gab.com Text Detecting hierarchical genome folding with network modularity JO: Nat Methods http://www.kidney.de/pget.php?&tw=1&pmid=29334377 #FOAvip Mammalian genomes are folded in a hierarchy of compartments, topologically associating domains (TADs), subTADs and looping interactions. Here, we describe 3DNetMod, a graph theory-based method for sensitive and accurate detection of chromatin domains across length scales in Hi-C data. We identify nested, partially overlapping TADs and subTADs genome wide by optimizing network modularity and varying a single resolution parameter. 3DNetMod can be applied broadly to understand genome reconfiguration in development and disease. Twit Text FOAVip Detecting hierarchical genome folding with network modularity ????Nat Methods http://www.kidney.de/pget.php?&tw=1&pmid=29334377 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29334377 #FOAvip English Wikipedia <ref>{{Cite pmid|29334377 }}</ref> Detecting hierarchical genome folding with network modularity #MMPMID29334377 Norton HK ; Emerson DJ ; Huang H ; Kim J ; Titus KR ; Gu S ; Bassett DS ; Phillips-Cremins JE Nat Methods 2018[Feb]; 15 (2 ): 119-122 PMID29334377 show ga Mammalian genomes are folded in a hierarchy of compartments, topologically associating domains (TADs), subTADs and looping interactions. Here, we describe 3DNetMod, a graph theory-based method for sensitive and accurate detection of chromatin domains across length scales in Hi-C data. We identify nested, partially overlapping TADs and subTADs genome wide by optimizing network modularity and varying a single resolution parameter. 3DNetMod can be applied broadly to understand genome reconfiguration in development and disease. |*Computer Graphics [MESH] |*Genome, Human [MESH] |Chromatin/*genetics/*metabolism [MESH] |Computational Biology/*methods [MESH] |High-Throughput Nucleotide Sequencing [MESH]Detecting hierarchical genome folding with network modularity (epmc).pdf DeepDyve Pubget Overpricing