Matt Raybould
@mijr12
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Postdoc in the Oxford Protein Informatics Group.
Oxford, England
Joined June 2017
RT @OPIGlets: Our paper "Transformers trained on proteins can learn to attend to Euclidean distance" is now published in @TmlrOrg @TmlrPub….
openreview.net
While conventional Transformers generally operate on sequence data, they can be used in conjunction with structure models, typically SE(3)-invariant or equivariant graph neural networks (GNNs), for...
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RT @AlissaHummer: Our work exploring the ability of and requirements for ML to predict the effects of mutations on antibody–antigen binding….
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RT @OPIGlets: Come and find OPIG at #PEGSummit today (Thursday). C089: LICHEN: Light-Chain Immunoglobulin Sequence Generation Conditioned o….
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RT @NeleQuast: Do you wish working with T-cell receptor structures was easier?.Us too!. STCRpy, our software suite for TCR structure parsin….
github.com
Contribute to npqst/STCRpy development by creating an account on GitHub.
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Was an honour for our collaboration with Sarosh Irani's group to be recognised with the PNAS Cozzarelli Prize #immunoinformatics #encephalitis #autoreactivity #bcells.
Join us in celebrating our 2024 Cozzarelli Prize Class IV: Biomedical Sciences winning paper, “Ultrahigh frequencies of peripherally matured LGI1- and CASPR2-reactive B cells characterize the cerebrospinal fluid in autoimmune encephalitis.” Read more:
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RT @OPIGlets: AntiFold, our antibody inverse folding model, has just been published at Bioinformatics Advances. Work led by @magnushoie & @….
github.com
Improved antibody structure-based design using inverse folding - oxpig/AntiFold
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RT @OPIGlets: We have released a web application for Humatch, our new antibody humanisation tool. Humatch enables experimental-like antib….
tandfonline.com
Antibodies are a popular and powerful class of therapeutic due to their ability to exhibit high affinity and specificity to target proteins. However, the majority of antibody therapeutics are not g...
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RT @ProfMilenkovic: This was a huge amount of work. Thanks to my Proceedings Co-Chair @kmborgwardt and all Area Chairs, reviewers, subrevie….
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RT @OPIGlets: Our manuscript "T-cell receptor structures and predictive models reveal comparable alpha and beta chain structural diversity….
nature.com
Communications Biology - T-cell receptor structures and predictions of deep learning models reveal comparable alpha and beta chain structural diversity despite differing genetic complexity.
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RT @OPIGlets: Happy 2025 from everyone at OPIG!. DPhil student Isaac Ellmen has written a News & Views article for Nature Chemical Biology….
nature.com
Nature Chemical Biology - Predicting protein structures from amino acid sequences used to be difficult and error prone. This changed in 2021 when AlphaFold2 reported near-experimental accuracy for...
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RT @NatureBiotech: AIntibody: an experimentally validated in silico antibody discovery design challenge https://t.c….
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RT @OPIGlets: OPIG DPhil student @oliverturnbull1 and postdocs @AlissaHummer & @mijr12 contributed computational profiling to a comparative….
tandfonline.com
Engineered antibody formats, such as antibody fragments and bispecifics, have the potential to offer improved therapeutic efficacy compared to traditional full-length monoclonal antibodies (mAbs). ...
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RT @NatureBiotech: Rapid discovery of monoclonal antibodies by microfluidics-enabled FACS of single pathogen-specific antibody-secreting ce….
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RT @OPIGlets: OPIG DPhil student @GemmaLGordon led work to build and analyse "PLAbDab-nano: a database of camelid and shark nanobodies from….
biorxiv.org
Nanobodies are essential proteins of the adaptive immune systems of camelid and shark species, complementing conventional antibodies. Properties such as their relatively small size, solubility and...
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