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10.1177/1535370217713750 http://scihub22266oqcxt.onion/10.1177/1535370217713750 C5529005!5529005 !28581336     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 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\28581336 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Exp+Biol+Med+(Maywood) 2017 ; 242 (13 ): 1325-1334 Nephropedia Template TP {{tp|p=28581336 |t=2017. Challenges and progress in interpretation of non-coding genetic variants associated with human disease |pdf=|usr=}}{{28581336 }} gab.com Text Challenges and progress in interpretation of non-coding genetic variants associated with human disease JO: Exp Biol Med (Maywood) http://www.kidney.de/pget.php?&tw=1&pmid=28581336 #FOAvip Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants. Twit Text FOAVip Challenges and progress in interpretation of non-coding genetic variants associated with human disease ????Exp Biol Med (Maywood) http://www.kidney.de/pget.php?&tw=1&pmid=28581336 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28581336 #FOAvip English Wikipedia <ref>{{Cite pmid|28581336 }}</ref> Challenges and progress in interpretation of non-coding genetic variants associated with human disease #MMPMID28581336 Zhu Y ; Tazearslan C ; Suh Y Exp Biol Med (Maywood) 2017[Jul]; 242 (13 ): 1325-1334 PMID28581336 show ga Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants. |*Epigenesis, Genetic [MESH] |*Genetic Predisposition to Disease [MESH] |*Genome-Wide Association Study [MESH] |Computational Biology/*methods [MESH] |Humans [MESH]Challenges and progress in interpretation of non-coding genetic varian(epmc).pdf DeepDyve Pubget Overpricing