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10.3389/fimmu.2018.01538 http://scihub22266oqcxt.onion/10.3389/fimmu.2018.01538 C6041393!6041393!30026743     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 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 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 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Front+Immunol 2018 ; 9 (ä): ä Nephropedia Template TP {{tp|p=30026743|t=2018. A Mechanistic Model for Predicting Cell Surface Presentation of Competing Peptides by MHC Class I Molecules |pdf=|usr=}}{{30026743}} gab.com Text A Mechanistic Model for Predicting Cell Surface Presentation of Competing Peptides by MHC Class I Molecules JO: Front Immunol http://www.kidney.de/pget.php?&tw=1&pmid=30026743 #FOAvip Major histocompatibility complex-I (MHC-I) molecules play a central role in the immune response to viruses and cancers. They present peptides on the surface of affected cells, for recognition by cytotoxic T cells. Determining which peptides are presented, and in what proportion, has profound implications for developing effective, medical treatments. However, our ability to predict peptide presentation levels is currently limited. Existing prediction algorithms focus primarily on the binding affinity of peptides to MHC-I, and do not predict the relative abundance of individual peptides on the surface of antigen-presenting cells in situ which is a critical parameter for determining the strength and specificity of the ensuing immune response. Here, we develop and experimentally verify a mechanistic model for predicting cell-surface presentation of competing peptides. Our approach explicitly models key steps in the processing of intracellular peptides, incorporating both peptide binding affinity and intracellular peptide abundance. We use the resulting model to predict how the peptide repertoire is modified by interferon-?, an immune modulator well known to enhance expression of antigen processing and presentation proteins. Twit Text FOAVip A Mechanistic Model for Predicting Cell Surface Presentation of Competing Peptides by MHC Class I Molecules ????Front Immunol http://www.kidney.de/pget.php?&tw=1&pmid=30026743 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=30026743 #FOAvip English Wikipedia <ref>{{Cite pmid|30026743}}</ref> A Mechanistic Model for Predicting Cell Surface Presentation of Competing Peptides by MHC Class I Molecules #MMPMID30026743 Boulanger DSM; Eccleston RC; Phillips A; Coveney PV; Elliott T; Dalchau N Front Immunol 2018[]; 9 (ä): ä PMID30026743show ga Major histocompatibility complex-I (MHC-I) molecules play a central role in the immune response to viruses and cancers. They present peptides on the surface of affected cells, for recognition by cytotoxic T cells. Determining which peptides are presented, and in what proportion, has profound implications for developing effective, medical treatments. However, our ability to predict peptide presentation levels is currently limited. Existing prediction algorithms focus primarily on the binding affinity of peptides to MHC-I, and do not predict the relative abundance of individual peptides on the surface of antigen-presenting cells in situ which is a critical parameter for determining the strength and specificity of the ensuing immune response. Here, we develop and experimentally verify a mechanistic model for predicting cell-surface presentation of competing peptides. Our approach explicitly models key steps in the processing of intracellular peptides, incorporating both peptide binding affinity and intracellular peptide abundance. We use the resulting model to predict how the peptide repertoire is modified by interferon-?, an immune modulator well known to enhance expression of antigen processing and presentation proteins. äA Mechanistic Model for Predicting Cell Surface Presentation of Compet(epmc).pdf DeepDyve Pubget Overpricing