首页|New Machine Learning Study Results Reported from Radboud University Nijmegen (Machine Learning Analysis of the T Cell Receptor Repertoire Identifies Sequence Features of Self-reactivity)
New Machine Learning Study Results Reported from Radboud University Nijmegen (Machine Learning Analysis of the T Cell Receptor Repertoire Identifies Sequence Features of Self-reactivity)
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A new study on Machine Learning is now available. According to news originating from Nijmegen, Netherlands, by NewsRx correspondents, research stated, “The T cell receptor (TCR) determines specificity and affinity for both foreign and self-peptides presented by the major histocompatibility complex (MHC). Although the strength of TCR interactions with self-pMHC impacts T cell function, it has been challenging to identify TCR sequence features that predict T cell fate.” Financial supporters for this research include Canadian Institutes of Health Research (CIHR), Tomlinson Doctoral Fellowship (McGill University), Natural Sciences and Engineering Research Council of Canada (NSERC), Natural Sciences and Engineering Research Council of Canada (NSERC), McGill start-up fund, Canadian Institutes of Health Research (CIHR), Netherlands Organization for Scientific Research (NWO), German Research Foundation (DFG), University of Lubeck.
NijmegenNetherlandsEuropeCyborgsEmerging TechnologiesMachine LearningRadboud University Nijmegen