Literature DB >> 18449989

Immunoinformatics and the in silico prediction of immunogenicity. An introduction.

Darren R Flower1.   

Abstract

Immunoinformatics is the application of informatics techniques to molecules of the immune system. One of its principal goals is the effective prediction of immunogenicity, be that at the level of epitope, subunit vaccine, or attenuated pathogen. Immunogenicity is the ability of a pathogen or component thereof to induce a specific immune response when first exposed to surveillance by the immune system, whereas antigenicity is the capacity for recognition by the extant machinery of the adaptive immune response in a recall response. In thisbook, we introduce these subjects and explore the current state of play in immunoinformatics and the in silico prediction of immunogenicity.

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Year:  2007        PMID: 18449989     DOI: 10.1007/978-1-60327-118-9_1

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  9 in total

1.  A mathematical model of the effect of immunogenicity on therapeutic protein pharmacokinetics.

Authors:  Xiaoying Chen; Timothy Hickling; Eugenia Kraynov; Bing Kuang; Chuenlei Parng; Paolo Vicini
Journal:  AAPS J       Date:  2013-08-30       Impact factor: 4.009

2.  T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges.

Authors:  Matthew N Davies; Darren R Flower; Kanchan Phadwal; Isabel K Macdonald; Peter V Coveney; Shunzhou Wan
Journal:  Immunome Res       Date:  2010-11-03

3.  BEST: improved prediction of B-cell epitopes from antigen sequences.

Authors:  Jianzhao Gao; Eshel Faraggi; Yaoqi Zhou; Jishou Ruan; Lukasz Kurgan
Journal:  PLoS One       Date:  2012-06-27       Impact factor: 3.240

Review 4.  Systems biology in vaccine design.

Authors:  Adrien Six; Bertrand Bellier; Véronique Thomas-Vaslin; David Klatzmann
Journal:  Microb Biotechnol       Date:  2011-12-21       Impact factor: 5.813

5.  EPMLR: sequence-based linear B-cell epitope prediction method using multiple linear regression.

Authors:  Yao Lian; Meng Ge; Xian-Ming Pan
Journal:  BMC Bioinformatics       Date:  2014-12-19       Impact factor: 3.169

Review 6.  Understanding infectious agents from an in silico perspective.

Authors:  Joo Chuan Tong; Lisa F P Ng
Journal:  Drug Discov Today       Date:  2010-10-23       Impact factor: 7.851

7.  Rapid identification of novel immunodominant proteins and characterization of a specific linear epitope of Campylobacter jejuni.

Authors:  Sebastian Hoppe; Frank F Bier; Markus von Nickisch-Rosenegk; Markus V Nickisch-Rosenegk
Journal:  PLoS One       Date:  2013-05-29       Impact factor: 3.240

8.  Epitope-Based Immunoinformatics Approach on Nucleocapsid Protein of Severe Acute Respiratory Syndrome-Coronavirus-2.

Authors:  Ahmed Rakib; Saad Ahmed Sami; Md Ashiqul Islam; Shahriar Ahmed; Farhana Binta Faiz; Bibi Humayra Khanam; Kay Kay Shain Marma; Maksuda Rahman; Mir Muhammad Nasir Uddin; Firzan Nainu; Talha Bin Emran; Jesus Simal-Gandara
Journal:  Molecules       Date:  2020-11-02       Impact factor: 4.411

Review 9.  Linear B-Cell Epitope Prediction for In Silico Vaccine Design: A Performance Review of Methods Available via Command-Line Interface.

Authors:  Kosmas A Galanis; Katerina C Nastou; Nikos C Papandreou; Georgios N Petichakis; Diomidis G Pigis; Vassiliki A Iconomidou
Journal:  Int J Mol Sci       Date:  2021-03-22       Impact factor: 5.923

  9 in total

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