Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
about
Mass Spectrometry of Human Leukocyte Antigen Class I Peptidomes Reveals Strong Effects of Protein Abundance and Turnover on Antigen PresentationNNAlign: a platform to construct and evaluate artificial neural network models of receptor-ligand interactions.Hammock: a hidden Markov model-based peptide clustering algorithm to identify protein-interaction consensus motifs in large datasets.A graph kernel approach for alignment-free domain-peptide interaction prediction with an application to human SH3 domainsUnsupervised HLA Peptidome Deconvolution Improves Ligand Prediction Accuracy and Predicts Cooperative Effects in Peptide-HLA Interactions.Identification of target-binding peptide motifs by high-throughput sequencing of phage-selected peptides.EPI-peptide designer: a tool for designing peptide ligand libraries based on epitope-paratope interactions.A machine learning strategy for predicting localization of post-translational modification sites in protein-protein interacting regionsSampling From the Proteome to the Human Leukocyte Antigen-DR (HLA-DR) Ligandome Proceeds Via High SpecificityDeciphering HLA-I motifs across HLA peptidomes improves neo-antigen predictions and identifies allostery regulating HLA specificity.Sarcoma Eradication by Doxorubicin and Targeted TNF Relies upon CD8+ T-cell Recognition of a Retroviral Antigen.High-resolution analysis of the murine MHC class II immunopeptidome.GibbsCluster: unsupervised clustering and alignment of peptide sequences.Unveiling the Peptide Motifs of HLA-C and HLA-G from Naturally Presented Peptides and Generation of Binding Prediction Matrices.The MHC Class II Immunopeptidome of Lymph Nodes in Health and in Chemically Induced Colitis.High-sensitivity HLA class I peptidome analysis enables a precise definition of peptide motifs and the identification of peptides from cell lines and patients' sera.Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry.Machine learning reveals a non-canonical mode of peptide binding to MHC class II molecules.Improved Prediction of Bovine Leucocyte Antigens (BoLA) Presented Ligands by Use of Mass-Spectrometry-Determined Ligand and in Vitro Binding Data.Purification of soluble HLA class I complexes from human serum or plasma deliver high quality immuno peptidomes required for biomarker discovery.NetMHCstab - predicting stability of peptide-MHC-I complexes; impacts for cytotoxic T lymphocyte epitope discovery.Development of a novel clustering tool for linear peptide sequencesGlobal pentapeptide statistics are far away from expected distributionsImmunopeptidomic Profiling of HLA-A2-Positive Triple Negative Breast Cancer Identifies Potential Immunotherapy Target Antigens
P2860
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P2860
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
description
2012 nî lūn-bûn
@nan
2012 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի հոտեմբերին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
@ast
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
@en
type
label
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
@ast
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
@en
prefLabel
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
@ast
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
@en
P2860
P50
P3181
P356
P1433
P1476
Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
@en
P2860
P3181
P356
10.1093/BIOINFORMATICS/BTS621
P407
P577
2012-10-24T00:00:00Z