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10.3389/fgene.2021.751158 http://scihub22266oqcxt.onion/10.3389/fgene.2021.751158 34858473!8632559!34858473     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Front+Genet 2021 ; 12 (ä): 751158 Nephropedia Template TP {{tp|p=34858473|t=2021. Identification of Intercellular Signaling Changes Across Conditions and Their Influence on Intracellular Signaling Response From Multiple Single-Cell Datasets |pdf=|usr=}}{{34858473}} gab.com Text Identification of Intercellular Signaling Changes Across Conditions and Their Influence on Intracellular Signaling Response From Multiple Single-Cell Datasets JO: Front Genet http://www.kidney.de/pget.php?&tw=1&pmid=34858473 #FOAvip Identification of intercellular signaling changes across multiple single-cell RNA-sequencing (scRNA-seq) datasets as well as how intercellular communications affect intracellular transcription factors (TFs) to regulate target genes is crucial in understanding how distinct cell states respond to evolution, perturbations, and diseases. Here, we first generalized our previously developed tool CellChat, enabling flexible comparison analysis of cell-cell communication networks across any number of scRNA-seq datasets from interrelated biological conditions. This greatly facilitates the ready detection of signaling changes of cell-cell communication in response to any biological perturbations. We then investigated how intercellular communications affect intracellular signaling response by inferring a multiscale signaling network which bridges the intercellular communications at the population level and the cell state-specific intracellular signaling network at the molecular level. The latter is constructed by integrating receptor-TF interactions collected from public databases and TF-target gene regulations inferred from a network-regularized regression model. By applying our approaches to three scRNA-seq datasets from skin development, spinal cord injury, and COVID-19, we demonstrated the capability of our approaches in identifying the predominant signaling changes across conditions and the critical signaling mechanisms regulating target gene expression. Together, our work will facilitate the identification of both intercellular and intracellular dysregulated signaling mechanisms responsible for biological perturbations in diverse tissues. Twit Text FOAVip Identification of Intercellular Signaling Changes Across Conditions and Their Influence on Intracellular Signaling Response From Multiple Single-Cell Datasets ????Front Genet http://www.kidney.de/pget.php?&tw=1&pmid=34858473 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34858473 #FOAvip English Wikipedia <ref>{{Cite pmid|34858473}}</ref> Identification of Intercellular Signaling Changes Across Conditions and Their Influence on Intracellular Signaling Response From Multiple Single-Cell Datasets #MMPMID34858473 Hao M; Zou X; Jin S Front Genet 2021[]; 12 (ä): 751158 PMID34858473show ga Identification of intercellular signaling changes across multiple single-cell RNA-sequencing (scRNA-seq) datasets as well as how intercellular communications affect intracellular transcription factors (TFs) to regulate target genes is crucial in understanding how distinct cell states respond to evolution, perturbations, and diseases. Here, we first generalized our previously developed tool CellChat, enabling flexible comparison analysis of cell-cell communication networks across any number of scRNA-seq datasets from interrelated biological conditions. This greatly facilitates the ready detection of signaling changes of cell-cell communication in response to any biological perturbations. We then investigated how intercellular communications affect intracellular signaling response by inferring a multiscale signaling network which bridges the intercellular communications at the population level and the cell state-specific intracellular signaling network at the molecular level. The latter is constructed by integrating receptor-TF interactions collected from public databases and TF-target gene regulations inferred from a network-regularized regression model. By applying our approaches to three scRNA-seq datasets from skin development, spinal cord injury, and COVID-19, we demonstrated the capability of our approaches in identifying the predominant signaling changes across conditions and the critical signaling mechanisms regulating target gene expression. Together, our work will facilitate the identification of both intercellular and intracellular dysregulated signaling mechanisms responsible for biological perturbations in diverse tissues. äIdentification of Intercellular Signaling Changes Across Conditions an(epmc).pdf DeepDyve Pubget Overpricing