ArticleImmunology2018
Development of a novel clustering tool for linear peptide sequences.
Article in Immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
57 citing papers in PubMed, 97 citations in OpenAlex.
- Computational structural dynamics and immunoinformatic analysis of EIEC IpaHMolecular diversity · 2026Article
- Cancer epitope prediction tools and analysis pipelines in CEDAR.Nucleic acids research · 2026Article
- Integrative immunoinformatics and structural modeling for the rational design of a multi-epitope vaccine candidate against human cytomegalovirus.Scientific reports · 2026Article
- Multi-strategy embedded framework for neoantigen vaccine maturation.Scientific reports · 2026Article
- The Cancer Epitope Database and Analysis Resource (CEDAR): current capabilities and future directions.Frontiers in oncology · 2026Review
- Article
- Computational modelling of a multiepitope vaccine targeting glycoprotein-D for herpes simplex virus 2 (HSV-2): an immunoinformatic analysis.Molecular diversity · 2025Article
- Topological deep learning for enhancing peptide-protein complex prediction.Communications chemistry · 2025Article
- Peptide clustering enhances large-scale analyses and reveals proteolytic signatures in mass spectrometry data.Nature communications · 2024Article
- Predicting immune response targets in orthoflaviviruses through sequence homology and computational analysis.Journal of molecular modeling · 2024Article
- Comparative membrane proteomic analysis of Tritrichomonas foetus isolates.Scientific reports · 2024Article
- Next-generation IEDB tools: a platform for epitope prediction and analysis.Nucleic acids research · 2024Article
- Design of a Multi-Epitope Vaccine againstJournal of fungi (Basel, Switzerland) · 2024Article
- Article
- Immunodominant conserved moieties on spike protein of SARS-CoV-2 renders virulence factor for the design of epitope-based peptide vaccines.Virusdisease · 2023Article
- Identification of cow milk epitopes to characterize and quantify disease-specific T cells in allergic children.The Journal of allergy and clinical immunology · 2023Article
- T cell reactivity to Bordetella pertussis is highly diverse regardless of childhood vaccination.Cell host & microbe · 2023Article
- Protein salvage and repurposing in evolution: Phospholipase D toxins are stabilized by a remodeled scrap of a membrane association domain.Protein science : a publication of the Protein Society · 2023Article
- Recent trends in next generation immunoinformatics harnessed for universal coronavirus vaccine design.Pathogens and global health · 2023Review
- Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Epitopes identified in large-scale screens of overlapping peptides often share significant levels of sequence identity, complicating the analysis of epitope-related data. Clustering algorithms are often used to facilitate these analyses, but available methods are generally insufficient in their capacity to define biologically meaningful epitope clusters in the context of the immune response. To fulfil this need we developed an algorithm that generates epitope clusters based on representative or consensus sequences. This tool allows the user to cluster peptide sequences on the basis of a specified level of identity by selecting among three different method options. These include the 'clique method', in which all members of the cluster must share the same minimal level of identity with each other, and the 'connected graph method', in which all members of a cluster must share a defined level of identity with at least one other member of the cluster. In cases where it is not possible to define a clear consensus sequence with the connected graph method, a third option provides a novel 'cluster-breaking algorithm' for consensus sequence driven sub-clustering. Herein we demonstrate the tool's clustering performance and applicability using (i) a selection of dengue virus epitopes for the 'clique method', (ii) sets of allergen-derived peptides from related species for the 'connected graph method' and (iii) large data sets of eluted ligand, major histocompatibility complex binding and T-cell recognition data captured within the Immune Epitope Database (IEDB) with the newly developed 'cluster-breaking algorithm'. This novel clustering tool is accessible at http://tools.iedb.org/cluster2/.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.