Encodings and models for antimicrobial peptide classification for multi-resistant pathogens-Reference-Cited by-同舟云学术

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Encodings and models for antimicrobial peptide classification for multi-resistant pathogens

Published:2019-03-04 Issue:1 Volume:12 Page:
ISSN:1756-0381
Container-title:BioData Mining
language:en
Short-container-title:BioData Mining

Author:

Spänig Sebastian,Heider Dominik

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Genetics,Molecular Biology,Biochemistry

Link

http://link.springer.com/content/pdf/10.1186/s13040-019-0196-x.pdf

Reference146 articles.

1. Mahlapuu M, Håkansson J, Ringstad L, Björn C. Antimicrobial Peptides: An Emerging Category of Therapeutic Agents. Front Cell Infect Microbiol. 2016;6:194.

2. Roca I, Akova M, Baquero F, Carlet J, Cavaleri M, Coenen S, et al. The global threat of antimicrobial resistance: science for intervention. New Microbes New Infect. 2015;6:22–9.

3. Nellums LB, Thompson H, Holmes A, Castro-Sánchez E, Otter JA, Norredam M, et al. Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis. Lancet Infect Dis. 2018;18:796–811.

4. Li Y, Xiang Q, Zhang Q, Huang Y, Su Z. Overview on the recent study of antimicrobial peptides: Origins, functions, relative mechanisms and application. Peptides. 2012;37:207–15.

5. LeCun Y, Bengio Y, Hinton G. Deep learning. Nature. 2015;521:436–44.

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