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10.1186/s12859-015-0529-9 http://scihub22266oqcxt.onion/10.1186/s12859-015-0529-9 C4450841!4450841 !25976669     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 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\25976669 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       BMC+Bioinformatics 2015 ; 16 (ä): 161 Nephropedia Template TP {{tp|p=25976669 |t=2015. Hierarchical decomposition of dynamically evolving regulatory networks |pdf=|usr=}}{{25976669 }} gab.com Text Hierarchical decomposition of dynamically evolving regulatory networks JO: BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=25976669 #FOAvip BACKGROUND: Gene regulatory networks describe the interplay between genes and their products. These networks control almost every biological activity in the cell through interactions. The hierarchy of genes in these networks as defined by their interactions gives important insights into how these functions are governed. Accurately determining the hierarchy of genes is however a computationally difficult problem. This problem is further complicated by the fact that an intrinsic characteristic of regulatory networks is that the wiring of interactions can change over time. Determining how the hierarchy in the gene regulatory networks changes with dynamically evolving network topology remains to be an unsolved challenge. RESULTS: In this study, we develop a new method, named D-HIDEN (Dynamic-HIerarchical DEcomposition of Networks) to find the hierarchy of the genes in dynamically evolving gene regulatory network topologies. Unlike earlier methods, which recompute the hierarchy from scratch when the network topology changes, our method adapts the hierarchy based on the wiring of the interactions only for the nodes which have the potential to move in the hierarchy. CONCLUSIONS: We compare D-HIDEN to five currently available hierarchical decomposition methods on synthetic and real gene regulatory networks. Our experiments demonstrate that D-HIDEN significantly outperforms existing methods in running time, accuracy, or both. Furthermore, our method is robust against dynamic changes in hierarchy. Our experiments on human gene regulatory networks suggest that our method may be used to reconstruct hierarchy in gene regulatory networks. Twit Text FOAVip Hierarchical decomposition of dynamically evolving regulatory networks ????BMC Bioinformatics http://www.kidney.de/pget.php?&tw=1&pmid=25976669 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=25976669 #FOAvip English Wikipedia <ref>{{Cite pmid|25976669 }}</ref> Hierarchical decomposition of dynamically evolving regulatory networks #MMPMID25976669 Ay A ; Gong D ; Kahveci T BMC Bioinformatics 2015[May]; 16 (ä): 161 PMID25976669 show ga BACKGROUND: Gene regulatory networks describe the interplay between genes and their products. These networks control almost every biological activity in the cell through interactions. The hierarchy of genes in these networks as defined by their interactions gives important insights into how these functions are governed. Accurately determining the hierarchy of genes is however a computationally difficult problem. This problem is further complicated by the fact that an intrinsic characteristic of regulatory networks is that the wiring of interactions can change over time. Determining how the hierarchy in the gene regulatory networks changes with dynamically evolving network topology remains to be an unsolved challenge. RESULTS: In this study, we develop a new method, named D-HIDEN (Dynamic-HIerarchical DEcomposition of Networks) to find the hierarchy of the genes in dynamically evolving gene regulatory network topologies. Unlike earlier methods, which recompute the hierarchy from scratch when the network topology changes, our method adapts the hierarchy based on the wiring of the interactions only for the nodes which have the potential to move in the hierarchy. CONCLUSIONS: We compare D-HIDEN to five currently available hierarchical decomposition methods on synthetic and real gene regulatory networks. Our experiments demonstrate that D-HIDEN significantly outperforms existing methods in running time, accuracy, or both. Furthermore, our method is robust against dynamic changes in hierarchy. Our experiments on human gene regulatory networks suggest that our method may be used to reconstruct hierarchy in gene regulatory networks. |*Algorithms [MESH] |*Cell Physiological Phenomena [MESH] |*Gene Regulatory Networks [MESH] |Cell Lineage [MESH] |Computational Biology/*methods [MESH] |Gene Expression Profiling [MESH] |Humans [MESH] |Lymphocytes/cytology/*metabolism [MESH]Hierarchical decomposition of dynamically evolving regulatory networks(epmc).pdf DeepDyve Pubget Overpricing