Multiple machine learning based descriptive and predictive workflow for the identification of potential PTP1B inhibitors-Reference-Cited by-同舟云学术

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Multiple machine learning based descriptive and predictive workflow for the identification of potential PTP1B inhibitors

Published:2017-01 Issue: Volume:71 Page:242-256
ISSN:1093-3263
Container-title:Journal of Molecular Graphics and Modelling
language:en
Short-container-title:Journal of Molecular Graphics and Modelling

Author:

Chandra Sharat,Pandey Jyotsana,Tamrakar Akhilesh Kumar,Siddiqi Mohammad Imran

Funder

CSIR network projects GENESIS

Publisher

Elsevier BV

Subject

Materials Chemistry,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Spectroscopy

Reference67 articles.

1. Insulin signalling and the regulation of glucose and lipid metabolism;Saltiel;Nature,2001

2. Disruption of IRS-2 causes type 2 diabetes in mice;Withers;Nature,1998

3. Protein tyrosine phosphatases in the human genome;Alonso;Cell,2004

4. Overexpression of protein-tyrosine phosphatase-1B in adipocytes inhibits insulin-stimulated phosphoinositide 3-kinase activity without altering glucose transport or Akt/protein kinase B activation;Venable;‎J. Biol. Chem.,2000

5. PTP1B antisense oligonucleotide lowers PTP1B protein, normalizes blood glucose, and improves insulin sensitivity in diabetic mice;Zinker;Proc. Natl. Acad. Sci. U.S.A.,2002

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