In Silico Approach for Prediction of Antifungal Peptides

This paper describes in silico models developed using a wide range of peptide features for predicting antifungal peptides (AFPs). Our analyses indicate that certain types of residue (e.g., C, G, H, K, R, Y) are more abundant in AFPs. The positional residue preference analysis reveals the prominence...

Descripción completa

Detalles Bibliográficos
Autores principales: Agrawal, Piyush, Bhalla, Sherry, Chaudhary, Kumardeep, Kumar, Rajesh, Sharma, Meenu, Raghava, Gajendra P. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Microbiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5834480/
https://www.ncbi.nlm.nih.gov/pubmed/29535692
http://dx.doi.org/10.3389/fmicb.2018.00323

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5834480/
https://www.ncbi.nlm.nih.gov/pubmed/29535692
http://dx.doi.org/10.3389/fmicb.2018.00323

Ejemplares similares