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Construction of biologically-interpretable chemical–disease association focused on transcription factors organizing chemically-perturbed genes

Year: 2021

Type: article

Abstract: Modification of disease-elicited gene expression is one of the core aspects in numerous drugs’ modes of action. To predict drug–disease associations, transcriptomics-based approaches with pathway analysis, graph theory and supervised machine learning-based calculation were developed. However, the pharmacological mechanism employed by drugs remain largely unknown.

Source: Proceedings for Annual Meeting of The Japanese Pharmacological Society

DOI: 10.1254/jpssuppl.94.0_1-y-e3-4

Authors: Zou Zhaonan, Michio Iwata, Yoshihiro Yamanishi, Shinya Oki

Institutions: Kyoto University, Kyushu Institute of Technology

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Drug Discovery

Field: Pharmacology, Toxicology and Pharmaceutics

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W3136630840

FWCI:

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