A graph attention–based deep learning network for predicting biotech–small-molecule drug interactions

The datasets and source code of this study are available in the GitHub repository: https://github.com/BioinformaticsIASBS/BSI-Net.

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Publication Details

Journal
Bioinformatics Advances
Published
2024-12-26
DOI
https://doi.org/10.1093/bioadv/vbaf192
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
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article

A graph attention–based deep learning network for predicting biotech–small-molecule drug interactions

Mohsen Hooshmand, Fatemeh Nasiri
Bioinformatics Advances
Computational Drug Discovery Methods
article

A graph attention–based deep learning network for predicting biotech–small-molecule drug interactions

Mohsen Hooshmand, Fatemeh Nasiri
article en

Abstract

The datasets and source code of this study are available in the GitHub repository: https://github.com/BioinformaticsIASBS/BSI-Net.

Bioinformatics AdvancesVol. 5(1)
Institute for Advanced Studies in Basic Sciences (IR)
Openalex Percentile: Top 67%
Computational Drug Discovery Methods
DOIOpen Access PDFOpenAlex
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A graph attention–based deep learning network for predicting biotech–small-molecule drug interactions — Mohsen Hooshmand, Fatemeh Nasiri · Bioinformatics Advances (2024) | TGRS Research Map | TGRS