Comparison of the Strengths and Weaknesses of Machine Learning Algorithms and Feature Selection on KEGG Database Microbial Gene Pathway Annotation and Its Effects on Reconstructed Network Topology-Reference-Cited by-同舟云学术

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Comparison of the Strengths and Weaknesses of Machine Learning Algorithms and Feature Selection on KEGG Database Microbial Gene Pathway Annotation and Its Effects on Reconstructed Network Topology

Published:2023-07-01 Issue:7 Volume:30 Page:766-782
ISSN:1557-8666
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Robben Michael¹^ORCID,Nasr Mohammad Sadegh¹,Das Avishek¹,Veerla Jai Prakash¹,Huber Manfred¹,Jaworski Justyn²,Weidanz Jon³,Luber Jacob¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, Texas, USA.

2. Department of Bioengineering, and University of Texas at Arlington, Arlington, Texas, USA.

3. Department of Kinesiology, University of Texas at Arlington, Arlington, Texas, USA.

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation

Link

https://www.liebertpub.com/doi/pdf/10.1089/cmb.2022.0370

Reference68 articles.

1. Whole-Genome Metagenomic Analysis of the Gut Microbiome in HIV-1-Infected Individuals on Antiretroviral Therapy

2. The MEME Suite

3. Beal J, Clore A, Manthey J. Studying pathogens degrades blast-based pathogen identification. bioRxiv 2022.

4. The InterPro protein families and domains database: 20 years on

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