Dataset 6 - Consensus Non-Haemolytic Antimicrobial Peptides Identified By Three Prediction Models (HemoPi, Macrel and MQSSM) From Peptidomes Derived From Cnidaria Omics Data
Published: 6 December 2024| Version 1 | DOI: 10.17632/dc5c6gb2w6.1
Contributors:
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Consensus approach using three prediction models (HemoPi, Macrel and MQSSM) to identify putative non-haemolytic antimicrobial peptides from peptidomes generated by in silico proteolysis of Cnidaria omics data.
Files
Steps to reproduce
1 - Three haemolytic prediction models - HemoPi (https://github.com/riteshcanfly/Hemopi) , MQSSM-I1 (Castillo-Mendieta, Kevin, et al. "A New Robust Method for Predicting Hemolytic Toxicity from Peptide Se-quence." (2023)) and Macrel (https://github.com/BigDataBiology/macrel) applied to the antimicrobial peptide libraries generated in "V1, doi: 10.17632/vn5mk4d44m.1" 2 - Construction of Venn Diagrams to identify the intersection of the three predicted datasets
Institutions
Universidade do Porto Centro Interdisciplinar de Investigacao Marinha e Ambiental, Universidad San Francisco de Quito Colegio de Ciencias de la Salud, Universidad Panamericana Aguascalientes Facultad de Ingenieria, Universidade do Porto Faculdade de Ciencias
Categories
Peptides, Biodiscovery, Omics, Antimicrobial