.png){kind=icon}
返回
Computational models, databases and tools for antibiotic combinations
.png){kind=icon}
PRE
AI
DOI：10.1093/bib/bbac309.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Antibiotic combination is a promising strategy to extend the lifetime of antibiotics and thereby combat antimicrobial resistance. However, screening for new antibiotic combinations is both time-consuming and labor-intensive. In recent years, an increasing number of researchers have used computational models to predict effective antibiotic combinations. In this review, we summarized existing computational models for antibiotic combinations and discussed the limitations and challenges of these models in detail. In addition, we also collected and summarized available data resources and tools for antibiotic combinations. This study aims to help computational biologists design more accurate and interpretable computational models.
Keyword:
antibiotic combinations
machine learning
complex network
synergy effect
databases
期刊
IF:
7.7
论文数:
5.8K
被引数:
2.7W
机构
引用论文
Uniaxial elongation of deswollen polydimethylsiloxane networks with supercoiled structure.png)
Polymer
PolymerIF0
PREAI
分享收藏Mechanisms of drug interactions between translation-inhibiting antibioticsNATURE COMMUNICATIONS
OAAI
NATURE COMMUNICATIONSIF15.7
OAAI分享收藏Network-based prediction of drug combinations (vol 10, 1197, 2019)基于网络的药物组合预测 (第10卷，1197，2019)NATURE COMMUNICATIONSOAAI
NATURE COMMUNICATIONSIF15.7
OAAI分享收藏Drug combinations: a strategy to extend the life of antibiotics in the 21 st century药物组合: 21世纪延长抗生素寿命的策略NATURE REVIEWS MICROBIOLOGY
NATURE REVIEWS MICROBIOLOGYIF103.3
PREAI
分享收藏
查看更多内容