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Mark M. Davis

Researcher at Stanford University

Publications -  623
Citations -  84251

Mark M. Davis is an academic researcher from Stanford University. The author has contributed to research in topics: T cell & T-cell receptor. The author has an hindex of 144, co-authored 581 publications receiving 74358 citations. Previous affiliations of Mark M. Davis include Washington University in St. Louis & University of Chicago.

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Model for the interaction of T-cell receptors with peptide/MHC complexes.

TL;DR: The immune response against a viral infection is mediated by two different types of cells known as B and T lymphocytes, which have specificity for a combination of foreign antigen with a molecule of the major histocompatibility complex (MHC).
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Genetic markers of the antigen-specific T cell receptor locus.

TL;DR: This study has shown that these two markers cosegregate in a set of BALB/c X SJL/J recombinant inbred mouse strains, permitting the conclusion that they are linked to within 3 centimorgans of each other, and to the kappa locus on chromosome 6.
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Analysis of a T cell receptor gene as a target of the somatic hypermutation mechanism.

TL;DR: The data indicate that although the TCR transgene is expressed in B cells, it is not efficiently targeted by the mutator mechanism, and the presence of an Ig H chain enhancer is itself not sufficient for targeting of the somatic hypermutation mechanism.
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SIMON, an Automated Machine Learning System, Reveals Immune Signatures of Influenza Vaccine Responses.

TL;DR: Simon, an automated machine learning system that compares results from 128 different algorithms and is particularly suitable for datasets containing many missing values, is applied to data from five clinical studies of seasonal influenza vaccination and reveals previously unrecognized CD4+ and T cell subsets strongly associated with a robust Ab response to influenza Ags.
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Recent progress in the analysis of αβT cell and B cell receptor repertoires.

TL;DR: Recent approaches and discoveries enabling advances in DNA sequencing technology and an array of complementary tools have now made their study much more tractable, filling a major gap in the ability to understand immunology as a system.