这使得对这些位置的考虑对于预测T细胞反应至关重要(图一)。 2023年4月7日,美国圣路易斯华盛顿大学Malachi和Obi Griffith研究组(https://griffithlab.org/)在Science Immunology发文题为:Computational prediction of MHC anchor locations guide neoantigen identification and prioritization(第一作者 夏慧明)。 为了预测不同...
这使得对这些位置的考虑对于预测T细胞反应至关重要(图一)。 2023年4月7日,美国圣路易斯华盛顿大学Malachi和Obi Griffith研究组(https://griffithlab.org/)在Science Immunology发文题为:Computational prediction of MHC anchor locations guide neo...
Synonyms Peptide-MHC binding affinity prediction ; Peptide-MHC binding prediction Definition Major histocompatibility complex (MHC) binders are short linear fragments of proteins that bind to MHC molecules for inspection by T-cell receptors (TCRs). T-cells recognize non-self antigens as peptide ...
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8. Sarkizova, S. et al. A large peptidome dataset improves HLA class I epitope prediction across most of the human population.Nat. Biotechnol.38, 199–209 (2020). 9. Luescher, I. F., Romero, P., Cerottini, J. C. & Maryanski, J. L. S...
(2004) MHC class I epitope binding prediction trained on small data sets. In, Proceedings for the third ICARIS meeting September 2004. Springer-Verlag, New York.Lundegaard,C. et al. (2004) MHC class I epitope binding prediction trained on small data sets. In Artificial Immune Systems, ...
3.5 通过结合切割母题和绑定母题改进MHC II配体预测。 Improved MHC II Ligand Prediction by Combining Cleavage Motifs and Binding Motifs 我们想看看将基于切割基序的评分与MHC结合预测相结合是否会提高预测MHC II配体的整体能力。 因此,我们将基于上面得出的切割概率得分的切割基序与先前建立的“ 7-等位基因方法”结...
Reliable and ultra-fast DNA and RNA sequencing have been achieved with the emergence of high-throughput sequencing technology. When combining the results of DNA and RNA sequencing for tumor cells of cancer patients, neoantigens that potentially stimulate
今天要介绍的是西奈山伊坎医学院遗传学和基因组科学系Timothy J. O'Donnell在Cell Systems上发表的论文” MHCflurry 2.0:Improved Pan-Allele Prediction of MHC Class I-Presented Peptides byIncorporating Antigen Processing”。主要组织相容性复合物(MHC,major histocompatibility complex)Ⅰ类蛋白与多肽的结合预测是研...
However, the number of known binders to a specific MHC molecule is limited in many cases, which poses a computational challenge for prediction of BNB and hence, needs improvement in learning of ANN. Here, we describe, the application of probability distribution functions to initialize the weights...