Uncovering PPAR-γ agonists: An integrated computational approach driven by machine learning-Reference-Cited by-同舟云学术

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Uncovering PPAR-γ agonists: An integrated computational approach driven by machine learning

Published:2024-06 Issue: Volume:129 Page:108742
ISSN:1093-3263
Container-title:Journal of Molecular Graphics and Modelling
language:en
Short-container-title:Journal of Molecular Graphics and Modelling

Author:

Haider Sajjad,Shafiq Muhammad,Siddiqui Ali Raza,Sardar Madiha,Mushtaq Mamona,Shafeeq Sehrish,Nur-e-Alam Mohammad,Ahmad Aftab,Ul-Haq Zaheer^ORCID

Funder

Higher Education Commission Pakistan

Publisher

Elsevier BV

Reference32 articles.

1. IDF diabetes atlas: estimation of global and regional gestational diabetes mellitus prevalence for 2021 by International Association of Diabetes in Pregnancy Study Group's Criteria;Wang;Diabetes Res. Clin. Pract.,2022

2. WHO Global report on diabetes: a summary;Roglic;Int. J. Noncommunicable Dis.,2016

3. Drug discovery of plausible lead natural compounds that target the insulin signaling pathway: bioinformatics approaches;Shanak;Evid. base Compl. Alternative Med.,2022

4. PPAR-Γ partial agonists in disease-fate decision with special reference to cancer;Ballav;Cells,2022

5. Peroxisome proliferator-activated receptors: regulation of transcriptional activities and roles in inflammation;Blanquart;J. Steroid Biochem. Mol. Biol.,2003

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