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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...
Autores principales: | Agrawal, Piyush, Bhalla, Sherry, Chaudhary, Kumardeep, Kumar, Rajesh, Sharma, Meenu, Raghava, Gajendra P. S. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
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 |
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