Subtask-Aware Representation Learning for Predicting Antibiotic Resistance Gene Properties via Gating-Controlled Mechanism

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成果类型：

期刊论文

作者：

Zhao, Weizhong;Wu, Junze;Luo, Shujie;Jiang, Xingpeng;He, Tingting;...

通讯作者：

Zhao, WZ

作者机构：

[Zhao, Weizhong; Zhao, WZ; He, Tingting; Jiang, Xingpeng; Wu, Junze; Luo, Shujie] Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smart, Wuhan 430079, Peoples R China.

[Zhao, Weizhong; Zhao, WZ; He, Tingting; Jiang, Xingpeng; Wu, Junze; Luo, Shujie] Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.

[Zhao, Weizhong; Zhao, WZ; He, Tingting; Jiang, Xingpeng; Wu, Junze; Luo, Shujie] Cent China Normal Univ, Natl Language Resources Monitoring & Res Ctr netwo, Wuhan 430079, Peoples R China.

[Hu, Xiaohua] Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA.

通讯机构：

[Zhao, WZ ] C

Cent China Normal Univ, Hubei Prov Key Lab Artificial Intelligence & Smart, Wuhan 430079, Peoples R China.

Cent China Normal Univ, Sch Comp, Wuhan 430079, Peoples R China.

Cent China Normal Univ, Natl Language Resources Monitoring & Res Ctr netwo, Wuhan 430079, Peoples R China.

语种：

英文

关键词：

Antibiotic resistance gene;multi-task learning;subtask-aware representation learning;gating-controlled mechanism

期刊：

IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS

ISSN：

2168-2194

年：

2024

卷：

期：

页码：

4348-4360

DOI：

10.1109/JBHI.2024.3390246

基金类别：

10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62372205 and 61932008) Fundamental Research Funds for Central Universities (Grant Number: KJ02502022-0450) National High-end Foreign Expert Cooperation Project (Grant Number: G2022158003L) Natural Science Foundation of Hubei Province of China (Grant Number: 2022CFB289)

机构署名：

本校为第一且通讯机构

院系归属：

计算机学院

摘要：

The crisis of antibiotic resistance has become a significant global threat to human health. Understanding properties of antibiotic resistance genes (ARGs) is the first step to mitigate this issue. Although many methods have been proposed for predicting properties of ARGs, most of these methods focus only on predicting antibiotic classes, while ignoring other properties of ARGs, such as resistance mechanisms and transferability. However, acquiring all of these properties of ARGs can help researchers gain a more comprehensive understanding of the essence of antibiotic resistance, which will faci...

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Subtask-Aware Representation Learning for Predicting Antibiotic Resistance Gene Properties via Gating-Controlled Mechanism

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