
doi: 10.1093/bib/bbl038
pmid: 17077136
T-cell recognition of peptide/major histocompatibility complex (MHC) is a prerequisite for cellular immunity. Recently, there has been an influx of bioinformatics tools to facilitate the identification of T-cell epitopes to specific MHC alleles. This article examines existing computational strategies for the study of peptide/MHC interactions. The most important bioinformatics tools and methods with relevance to the study of peptide/MHC interactions have been reviewed. We have also provided guidelines for predicting antigenic peptides based on the availability of existing experimental data.
Binding Sites, Epitopes, T-Lymphocyte, Antigen-Antibody Complex, Antigens/peptides/epitopes, 004, HLA Antigens, Sequence Analysis, Protein, Protein Interaction Mapping, MHC, Prediction, Peptides, Algorithms, Epitope Mapping, Protein Binding
Binding Sites, Epitopes, T-Lymphocyte, Antigen-Antibody Complex, Antigens/peptides/epitopes, 004, HLA Antigens, Sequence Analysis, Protein, Protein Interaction Mapping, MHC, Prediction, Peptides, Algorithms, Epitope Mapping, Protein Binding
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 88 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
