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10.1038/srep14577 http://scihub22266oqcxt.onion/10.1038/srep14577 C4602215!4602215 !26459019     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26459019 &cmd=llinks): Failed to open stream: HTTP request failed! 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Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control |pdf=|usr=}}{{26459019 }} gab.com Text Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=26459019 #FOAvip Deciphering the association between life molecules and human diseases is currently an important task in systems biology. Research over the past decade has unveiled that the human genome is almost entirely transcribed, producing a vast number of non-protein-coding RNAs (ncRNAs) with potential regulatory functions. More recent findings suggest that many diseases may not be exclusively linked to mutations in protein-coding genes. The combination of these arguments poses the question of whether ncRNAs that play a critical role in network control are also enriched with disease-associated ncRNAs. To address this question, we mapped the available annotated information of more than 350 human disorders to the largest collection of human ncRNA-protein interactions, which define a bipartite network of almost 93,000 interactions. Using a novel algorithmic-based controllability framework applied to the constructed bipartite network, we found that ncRNAs engaged in critical network control are also statistically linked to human disorders (P-value of P = 9.8 × 10(-109)). Taken together, these findings suggest that the addition of those genes that encode optimized subsets of ncRNAs engaged in critical control within the pool of candidate genes could aid disease gene prioritization studies. Twit Text FOAVip Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=26459019 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26459019 #FOAvip English Wikipedia <ref>{{Cite pmid|26459019 }}</ref> Determining Associations between Human Diseases and non-coding RNAs with Critical Roles in Network Control #MMPMID26459019 Kagami H ; Akutsu T ; Maegawa S ; Hosokawa H ; Nacher JC Sci Rep 2015[Oct]; 5 (ä): 14577 PMID26459019 show ga Deciphering the association between life molecules and human diseases is currently an important task in systems biology. Research over the past decade has unveiled that the human genome is almost entirely transcribed, producing a vast number of non-protein-coding RNAs (ncRNAs) with potential regulatory functions. More recent findings suggest that many diseases may not be exclusively linked to mutations in protein-coding genes. The combination of these arguments poses the question of whether ncRNAs that play a critical role in network control are also enriched with disease-associated ncRNAs. To address this question, we mapped the available annotated information of more than 350 human disorders to the largest collection of human ncRNA-protein interactions, which define a bipartite network of almost 93,000 interactions. Using a novel algorithmic-based controllability framework applied to the constructed bipartite network, we found that ncRNAs engaged in critical network control are also statistically linked to human disorders (P-value of P = 9.8 × 10(-109)). Taken together, these findings suggest that the addition of those genes that encode optimized subsets of ncRNAs engaged in critical control within the pool of candidate genes could aid disease gene prioritization studies. |*Gene Expression Regulation [MESH] |*Gene Regulatory Networks [MESH] |*Genetic Association Studies [MESH] |*Genetic Predisposition to Disease [MESH] |Humans [MESH] |Models, Biological [MESH] |Protein Binding [MESH] |RNA, Untranslated/*genetics [MESH]Determining Associations between Human Diseases and non-coding RNAs wi(epmc).pdf DeepDyve Pubget Overpricing