PEASE specifications

Information


Unique identifier OMICS_06750
Name PEASE
Alternative name Predicting Epitopes using Antibody SEquence
Interface Web user interface
Restrictions to use None
Computer skills Basic
Stability Stable
Maintained Yes

Publication for Predicting Epitopes using Antibody SEquence

PEASE citations

 (2)
library_books

Fundamentals and Methods for T and B Cell Epitope Prediction

2017
J Immunol Res
PMCID: 5763123
PMID: 29445754
DOI: 10.1155/2017/2680160

[…] zyk et al. [] developed EpiPred, a method that uses a docking-like approach to match up antibody and antigen structures, thus identifying epitope regions on the antigen. A similar approach is used by PEASE [], adding that this method utilizes the sequence of the antibody and the 3D-structure of the antigen. Briefly, for each pair of antibody sequence and antigen structure, PEASE uses a machine lea […]

library_books

An Introduction to B Cell Epitope Mapping and In Silico Epitope Prediction

2016
J Immunol Res
PMCID: 5227168
PMID: 28127568
DOI: 10.1155/2016/6760830

[…] ed to rigid-body docking algorithms, EpiPred significantly enriches the number of close-to-native decoys when adjusting the Ab sequence against the Ag [].Predicting Epitopes Using Antibody Sequences (PEASE) evaluates a pair score for all combinations of one residue from the complementarity determining regions (CDR) of antibody and one residue from the surface exposed region of antigen. A residue s […]

PEASE institution(s)
The Goodman Faculty of Life Sciences, Nanotechnology Building, Bar-Ilan University, Ramat-Gan, Israel; Division of Vaccine Discovery, La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA

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