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dc.contributor.author
Hansen, Christian Skjødt  
dc.contributor.author
Østerbye, Thomas  
dc.contributor.author
Marcatili, Paolo  
dc.contributor.author
Lund, Ole  
dc.contributor.author
Buus, Søren  
dc.contributor.author
Nielsen, Morten  
dc.date.available
2018-06-14T14:48:40Z  
dc.date.issued
2017-01  
dc.identifier.citation
Hansen, Christian Skjødt; Østerbye, Thomas; Marcatili, Paolo; Lund, Ole; Buus, Søren; et al.; ArrayPitope: Automated analysis of amino acid substitutions for peptide microarray-based antibody epitope mapping; Public Library of Science; Plos One; 12; 1; 1-2017  
dc.identifier.issn
1932-6203  
dc.identifier.uri
http://hdl.handle.net/11336/48623  
dc.description.abstract
Identification of epitopes targeted by antibodies (B cell epitopes) is of critical importance for the development of many diagnostic and therapeutic tools. For clinical usage, such epitopes must be extensively characterized in order to validate specificity and to document potential cross-reactivity. B cell epitopes are typically classified as either linear epitopes, i.e. short consecutive segments from the protein sequence or conformational epitopes adapted through native protein folding. Recent advances in high-density peptide microarrays enable high-throughput, highresolution identification and characterization of linear B cell epitopes. Using exhaustive amino acid substitution analysis of peptides originating from target antigens, these microarrays can be used to address the specificity of polyclonal antibodies raised against such antigens containing hundreds of epitopes. However, the interpretation of the data provided in such largescale screenings is far from trivial and in most cases it requires advanced computational and statistical skills. Here, we present an online application for automated identification of linear B cell epitopes, allowing the non-expert user to analyse peptide microarray data. The application takes as input quantitative peptide data of fully or partially substituted overlapping peptides from a given antigen sequence and identifies epitope residues (residues that are significantly affected by substitutions) and visualize the selectivity towards each residue by sequence logo plots. Demonstrating utility, the application was used to identify and address the antibody specificity of 18 linear epitope regions in Human Serum Albumin (HSA), using peptide microarray data consisting of fully substituted peptides spanning the entire sequence of HSA and incubated with polyclonal rabbit anti-HSA (and mouse anti-rabbit-Cy3). The application is made available at: www.cbs.dtu.dk/services/ArrayPitope.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Public Library of Science  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Antibody  
dc.subject
Peptide Array  
dc.subject
Motif  
dc.subject.classification
Salud Ocupacional  
dc.subject.classification
Ciencias de la Salud  
dc.subject.classification
CIENCIAS MÉDICAS Y DE LA SALUD  
dc.title
ArrayPitope: Automated analysis of amino acid substitutions for peptide microarray-based antibody epitope mapping  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2018-06-13T14:58:15Z  
dc.journal.volume
12  
dc.journal.number
1  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
San Francisco  
dc.description.fil
Fil: Hansen, Christian Skjødt. Technical University of Denmark; Dinamarca  
dc.description.fil
Fil: Østerbye, Thomas. Universidad de Copenhagen; Dinamarca  
dc.description.fil
Fil: Marcatili, Paolo. Technical University of Denmark; Dinamarca  
dc.description.fil
Fil: Lund, Ole. Technical University of Denmark; Dinamarca  
dc.description.fil
Fil: Buus, Søren. Universidad de Copenhagen; Dinamarca  
dc.description.fil
Fil: Nielsen, Morten. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Biotecnológicas. Universidad Nacional de San Martín. Instituto de Investigaciones Biotecnológicas; Argentina  
dc.journal.title
Plos One  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/https://dx.doi.org/10.1371/journal.pone.0168453  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0168453