Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/8617
Title: DeepGrep: A deep convolutional neural network for predicting gene-regulating effects of small molecules
Authors: Bardak B.
Tan, Mehmet
Keywords: Chemical-induced
Deep neural networks
Gene expression
Convolution
Convolutional neural networks
Deep neural networks
Forecasting
Molecules
Baseline models
Chemical-induced
Chemogenomics
Differential gene expressions
Gene expression effects
Gene-regulation
Genes expression
In-silico
Learning models
Small molecules
Gene expression
Issue Date: 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Bardak, B., & Tan, M. (2021, October). DeepGREP: A deep convolutional neural network for predicting gene-regulating effects of small molecules. In 2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) (pp. 1-8). IEEE.
Abstract: Accurately predicting desired gene expression effects by using the representations of drugs and genes in silico is a key task in chemogenomics. This paper proposes DeepGREP, a deep learning model that can predict small molecules’ gene regulation effects. The main motivation of this work is improving chemical-induced differential gene expression prediction by using a convolutional-based architecture to represent drugs and genes more effectively. To evaluate the performance of the DeepGREP, we conducted several experiments and compared them with DeepCop, the baseline model. The results show that DeepGREP outperforms the baseline model and significantly improves the gene expression prediction for AUC by around 4%, F-Score by around 15%, and Enrichment Factor by around 22%. We also demonstrate that the proposed method mostly outperforms the baseline in more difficulties setting of generalization to unseen molecules by using cold-drug splitting. © 2021 IEEE.
Description: 2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2021 -- 13 October 2021 through 15 October 2021 -- -- 176925
URI: https://doi.org/10.1109/CIBCB49929.2021.9562920
https://hdl.handle.net/20.500.11851/8617
ISBN: 9781665401128
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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