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Chan2004_TCell_receptor_activation


ABSTRACT: The model reproduces Fig 3a of the paper. Please note that the authors mention that they used a value of 2 for n, n being the power in the positive feedback function for kinase autocatalysis, however the model here has n=1.95 because this results in a simulation that is identical to Fig 3a. The model was successfully tested on MathSBML. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information. In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not. To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

DISEASE(S): Bacterial Infectious Disease

SUBMITTER: Harish Dharuri  

PROVIDER: BIOMD0000000120 | BioModels | 2024-09-02

REPOSITORIES: BioModels

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Publications

Feedback control of T-cell receptor activation.

Chan Cliburn C   Stark Jaroslav J   George Andrew J T AJ  

Proceedings. Biological sciences 20040501 1542


The specificity and sensitivity of T-cell recognition is vital to the immune response. Ligand engagement with the T-cell receptor (TCR) results in the activation of a complex sequence of signalling events, both on the cell membrane and intracellularly. Feedback is an integral part of these signalling pathways, yet is often ignored in standard accounts of T-cell signalling. Here we show, using a mathematical model, that these feedback loops can explain the ability of the TCR to discriminate betwe  ...[more]

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