Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Building a meta-predictor for MHC class II-binding peptides.

Methods in molecular biology (Clifton, N.J.) - 1 Jan 2007

Huang Lei, Karpenko Oleksiy, Murugan Naveen, Dai Yang

Abstract excerpt

Prediction of class II major histocompatibility complex (MHC)-peptide binding is a challenging task due to variable length of binding peptides. Different computational methods have been developed; however, each has its own strength and weakness. In order to provide reliable prediction, it is important to design a system that enables the integration of outcomes from various predictors. In this chapter, the...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Bayes Theorem
Share to Epitopes
Share to Histocompatibility Antigens Class II

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to HLA-DR Antigens

Share to HLA-DRB1 Chains

Share to Immunogenetics

Share to Major Histocompatibility Complex

Share to Peptides

Source

Identifiers

PMID: 18450014
DOI: 10.1007/978-1-60327-118-9_26

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Building a meta-predictor for MHC class II-binding peptides.PMID 18450014Read ↗

A meta-predictor for MHC class II binding peptides based on Naïve Bayesian approach.Semantic proximity Read ↗

Application of machine learning techniques in predicting MHC binders.Semantic proximity Read ↗

Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules.Semantic proximity Read ↗

Machine Learning Methods for Predicting HLA-Peptide Binding ActivitySemantic proximity Read ↗

Methods for Prediction of Peptide Binding to MHC Molecules: A Comparative StudySemantic proximity Read ↗

Toward more accurate pan-specific MHC-peptide binding prediction: a review of current methods and tools.Semantic proximity Read ↗

Prediction of binding to MHC class I moleculesSemantic proximity Read ↗

A novel predictive technique for the MHC class II peptide-binding interaction.Semantic proximity Read ↗

Machine learning predictions of MHC-II specificities reveal alternative binding mode of class II epitopesSemantic proximity Read ↗

A practical guide to structure-based prediction of MHC-binding peptides.Semantic proximity Read ↗

Predicting peptide presentation by major histocompatibility complex class I using one million peptidesSemantic proximity Read ↗

Performance Evaluation of MHC Class-I Binding Prediction Tools Based on an Experimentally Validated MHC–Peptide Binding Data SetSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.