Interactome-Based Machine Learning Predicts Potential Therapeutics for COVID-19-Reference-Cited by-同舟云学术

Interactome-Based Machine Learning Predicts Potential Therapeutics for COVID-19

Published:2023-04-04 Issue:15 Volume:8 Page:13840-13854
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Ghosh Nimisha¹²^ORCID,Saha Indrajit³,Gambin Anna¹

Affiliation:

1. Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, 00-927 Warsaw, Poland

2. Department of Computer Science and Information Technology, Institute of Technical Education and Research, Siksha ‘O’ Anusandhan, Bhubaneswar, 751030 Odisha, India

3. Department of Computer Science and Engineering, National Institute of Technical Teachers’ Training and Research, Kolkata, 700106 West Bengal, India

Funder

European Research Consortium for Informatics and Mathematics

Department of Science and Technology, Ministry of Science and Technology

Uniwersytet Warszawski

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.3c00030

Reference69 articles.

1. Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry

2. The two-hybrid system: an assay for protein-protein interactions

3. A comprehensive two-hybrid analysis to explore the yeast protein interactome

4. Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae

5. A two-step framework for inferring direct protein-protein interaction network from AP-MS data

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