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10.1038/s41598-018-21945-2 http://scihub22266oqcxt.onion/10.1038/s41598-018-21945-2 C5827039!5827039 !29483553     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 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\29483553 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Sci+Rep 2018 ; 8 (1 ): 3594 Nephropedia Template TP {{tp|p=29483553 |t=2018. Network Motifs Capable of Decoding Transcription Factor Dynamics |pdf=|usr=}}{{29483553 }} gab.com Text Network Motifs Capable of Decoding Transcription Factor Dynamics JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=29483553 #FOAvip Transcription factors (TFs) can encode the information of upstream signal in terms of its temporal activation dynamics. However, it remains unclear how different types of TF dynamics are decoded by downstream signalling networks. In this work, we studied all three-node transcriptional networks for their ability to distinguish two types of TF dynamics: amplitude modulation (AM), where the TF is activated with a constant amplitude, and frequency modulation (FM), where the TF activity displays an oscillatory behavior. We found two sets of network topologies: one set can differentially respond to AM TF signal but not to FM; the other set to FM signal but not to AM. Interestingly, there is little overlap between the two sets. We identified the prevalent topological features in each set and gave a mechanistic explanation as to why they can differentially respond to only one type of TF signal. We also found that some network topologies have a weak (not robust) ability to differentially respond to both AM and FM input signals by using different values of parameters for AM and FM cases. Our results provide a novel network mechanism for decoding different TF dynamics. Twit Text FOAVip Network Motifs Capable of Decoding Transcription Factor Dynamics ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=29483553 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29483553 #FOAvip English Wikipedia <ref>{{Cite pmid|29483553 }}</ref> Network Motifs Capable of Decoding Transcription Factor Dynamics #MMPMID29483553 Gao Z ; Chen S ; Qin S ; Tang C Sci Rep 2018[Feb]; 8 (1 ): 3594 PMID29483553 show ga Transcription factors (TFs) can encode the information of upstream signal in terms of its temporal activation dynamics. However, it remains unclear how different types of TF dynamics are decoded by downstream signalling networks. In this work, we studied all three-node transcriptional networks for their ability to distinguish two types of TF dynamics: amplitude modulation (AM), where the TF is activated with a constant amplitude, and frequency modulation (FM), where the TF activity displays an oscillatory behavior. We found two sets of network topologies: one set can differentially respond to AM TF signal but not to FM; the other set to FM signal but not to AM. Interestingly, there is little overlap between the two sets. We identified the prevalent topological features in each set and gave a mechanistic explanation as to why they can differentially respond to only one type of TF signal. We also found that some network topologies have a weak (not robust) ability to differentially respond to both AM and FM input signals by using different values of parameters for AM and FM cases. Our results provide a novel network mechanism for decoding different TF dynamics. |*Gene Regulatory Networks [MESH] |*Models, Theoretical [MESH] |Animals [MESH] |Computational Biology/methods [MESH] |Data Analysis [MESH] |Feedback, Physiological [MESH] |Gene Expression Regulation [MESH] |Half-Life [MESH] |Humans [MESH] |Proteins/genetics/metabolism [MESH] |Signal Transduction/*genetics [MESH]Network Motifs Capable of Decoding Transcription Factor Dynamics (epmc).pdf DeepDyve Pubget Overpricing