ReviewFEBS letters2010
Computational analysis of T cell receptor signaling and ligand discrimination--past, present, and future.
Review in FEBS letters, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- How the T cell signaling network processes information to discriminate between self and agonist ligands.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- TCR-pMHC bond conformation controls TCR ligand discrimination.Cellular & molecular immunology · 2020Article
- Article
- Slow phosphorylation of a tyrosine residue in LAT optimizes T cell ligand discrimination.Nature immunology · 2019Article
- Understanding the Dynamics of T-Cell Activation in Health and Disease Through the Lens of Computational Modeling.JCO clinical cancer informatics · 2019Review
- Immunological Paradigms, Mechanisms, and Models: Conceptual Understanding Is a Prerequisite to Effective Modeling.Frontiers in immunology · 2019Review
- Regulatory mechanisms in T cell receptor signalling.Nature reviews. Immunology · 2018Review
- Chemical Control over T-Cell Activation in Vivo Using Deprotection of trans-Cyclooctene-Modified Epitopes.ACS chemical biology · 2018Article
- The role of bioinformatics in studying rheumatic and autoimmune disorders.Nature reviews. Rheumatology · 2011Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Signaling through the T cell receptor for antigen (TCR) has been studied for years by conventional biochemical means. More recently, attempts have been made to develop computational models of signaling through this receptor, with a specific focus on understanding how this recognition system discriminates between closely related (self and non-self) ligands. Here we discuss recent advances centered on the role of feedback regulation, especially the key finding that a combination of digital and analog control circuits is fundamental to the discrimination properties of the TCR. We end by pointing to future, more biologically accurate models that incorporate spatial aspects of molecular organization in antigen-engaged T lymphocytes with this underlying biochemistry.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.