OxASN: The Oxford Antigen Specificity Network

362 posts

OxASN: The Oxford Antigen Specificity Network banner
OxASN: The Oxford Antigen Specificity Network

OxASN: The Oxford Antigen Specificity Network

@Ox_T_Cell_ASN

OxASN is a multidisciplinary network of scientists with the common gaol of decoding the principles of antigen specific cellular immunity in time and space.

University of Oxford Katılım Şubat 2023
245 Takip Edilen346 Takipçiler
OxASN: The Oxford Antigen Specificity Network retweetledi
Nature Rev Immunol
Nature Rev Immunol@NatRevImmunol·
A role for CD8+ T cells in lupus nephritis dlvr.it/TSWLDP
English
0
16
41
3.7K
OxASN: The Oxford Antigen Specificity Network retweetledi
OxASN: The Oxford Antigen Specificity Network retweetledi
Adrian Liston
Adrian Liston@LabListon·
Our new book "Self-Doubt" is written by scientists for scientists. You might think you are alone when you doubt your ability or suitability for science - you aren't. We all question ourselves and carry doubt with us daily. amazon.com/Self-Doubt-Ant…
English
2
6
27
3.8K
OxASN: The Oxford Antigen Specificity Network retweetledi
Mikhail Shugay
Mikhail Shugay@antigenomics·
T-SCAPE: T cell immunogenicity scoring via cross-domain aided predictive engine science.org/doi/full/10.11…
Mikhail Shugay tweet media
English
0
6
28
2.3K
OxASN: The Oxford Antigen Specificity Network retweetledi
Mikhail Shugay
Mikhail Shugay@antigenomics·
Assessment of computational methods in predicting TCR–epitope binding recognition, Lu et al. @naturemethods: "Our analysis revealed that the source of negative TCRs substantially impacts model accuracy, with external negatives potentially introducing uncontrolled confounders. Model performance generally improved with more TCRs per epitope, highlighting the importance of large and diverse datasets. Models incorporating multiple features typically outperformed those using only complementarity-determining region 3β information, yet all struggle to generalize to unseen epitopes. The use of independent test sets proved crucial for unbiased assessment on both seen and unseen epitopes. " nature.com/articles/s4159…
English
0
4
24
3.7K
Klebanoff_Lab
Klebanoff_Lab@KlebanoffLab·
🤯Three (!!!) new papers today in @ScienceMagazine on the application of generative AI for the de novo design of peptide/HLA binding molecules! Completely unique 3D structure and binding mode compared with natural TCRs and TCR mimics! Links to papers 👇
Klebanoff_Lab tweet media
English
8
132
674
80.4K