Dataset 11- Union And Intersection Datasets Of The Predicted Antibacterial, Antiviral, Antifungal And Anticancer Peptides From Cnidaria Omics Data

Published: 6 December 2024| Version 1 | DOI: 10.17632/8vbphryhp4.1
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Description

Compilation of the antibacterial, antiviral, antifungal and anticancer peptides intersection and union datasets obtained with three prediction models

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Steps to reproduce

The following prediction tools were applied to the union dataset of the 1,935 most representative Cnidara Singular AMPs from "Mendeley Data, V1, doi: 10.17632/gdrn9sypx4.1": 1 - iAMPCN (https://github.com/joy50706/iAMPCN) was used to predict ABPs (antibacterial), AFPs (antifungal), AVPs (antiviral) and ACP (anticancer) peptides 2 - AMPDiscover (https://biocom-ampdiscover.cicese.mx/) was used to predict ABPs, AFPs and AVPs 3 - AntiBP3 (https://github.com/raghavagps/AntiBP3/blob/main/README.md) was used to predict ABPs 3 - AI4AVP (https://github.com/LinTzuTang/AI4AVP_predictor) was used to predict AVPs 4 - Antifp (https://webs.iiitd.edu.in/raghava/antifp/algo.php) was used to predict AFPs 5 - AntiCP 2.0 (https://webs.iiitd.edu.in/raghava/anticp2/) and ModlAMP (https://modlamp.org/) was used to predict ACPs 6 - Construction of Venn Diagrams to identify the intersection and union of the three predicted datasets for each activity

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

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