DILIrank：按人类发生药物性肝损伤风险排序的最大参考药物清单。 - Suppr

DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans.

作者信息

Chen Minjun, Suzuki Ayako, Thakkar Shraddha, Yu Ke, Hu Chuchu, Tong Weida

机构信息

Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA.

Department of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.

出版信息

Drug Discov Today. 2016 Apr;21(4):648-53. doi: 10.1016/j.drudis.2016.02.015. Epub 2016 Mar 3.

DOI:10.1016/j.drudis.2016.02.015

PMID:26948801

Abstract

摘要

相似文献

DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans.DILIrank：按人类发生药物性肝损伤风险排序的最大参考药物清单。

Drug Discov Today. 2016 Apr;21(4):648-53. doi: 10.1016/j.drudis.2016.02.015. Epub 2016 Mar 3.

Drug-induced liver injury severity and toxicity (DILIst): binary classification of 1279 drugs by human hepatotoxicity.药物性肝损伤严重程度和毒性（DILIst）：1279 种药物的人类肝毒性的二进制分类。

Drug Discov Today. 2020 Jan;25(1):201-208. doi: 10.1016/j.drudis.2019.09.022. Epub 2019 Nov 1.

Computational Models Using Multiple Machine Learning Algorithms for Predicting Drug Hepatotoxicity with the DILIrank Dataset.使用多种机器学习算法的计算模型，结合 DILIrank 数据集预测药物肝毒性。

Int J Mol Sci. 2020 Mar 19;21(6):2114. doi: 10.3390/ijms21062114.

Hepatotoxicity by Drugs: The Most Common Implicated Agents.药物性肝损伤：最常见的致病药物。

Int J Mol Sci. 2016 Feb 6;17(2):224. doi: 10.3390/ijms17020224.

FDA-approved drug labeling for the study of drug-induced liver injury.FDA 批准用于药物性肝损伤研究的药物标签。

Drug Discov Today. 2011 Aug;16(15-16):697-703. doi: 10.1016/j.drudis.2011.05.007. Epub 2011 May 20.

Quantitative structure-activity relationship models for predicting drug-induced liver injury based on FDA-approved drug labeling annotation and using a large collection of drugs.基于 FDA 批准药物标签注释和大量药物的用于预测药物性肝损伤的定量构效关系模型。

Toxicol Sci. 2013 Nov;136(1):242-9. doi: 10.1093/toxsci/kft189. Epub 2013 Aug 31.

[Drug-induced liver lesions].[药物性肝损伤]

Med Welt. 1978 Apr 7;29(14):559-66.

Drug-induced liver injury: Diagnosing (and treating) it early.药物性肝损伤：早期诊断（及治疗）。

J Fam Pract. 2015 Oct;64(10):634-44.

How to end med confusion.如何终结用药困惑。

Hosp Health Netw. 2007 Jan;81(1):8, 10.

Prediction methods and databases within chemoinformatics: emphasis on drugs and drug candidates.化学信息学中的预测方法与数据库：重点关注药物及候选药物

Bioinformatics. 2005 May 15;21(10):2145-60. doi: 10.1093/bioinformatics/bti314. Epub 2005 Feb 15.

引用本文的文献

A multi-dimensional computational framework of drug-induced hepatotoxicity: integrating molecular structure features with disease pathogenesis.药物性肝毒性的多维计算框架：将分子结构特征与疾病发病机制相结合。

Brief Bioinform. 2025 Aug 31;26(5). doi: 10.1093/bib/bbaf456.

Drug-induced liver injury prediction based on graph convolutional networks and toxicogenomics.基于图卷积网络和毒理基因组学的药物性肝损伤预测

PLoS Comput Biol. 2025 Sep 5;21(9):e1013423. doi: 10.1371/journal.pcbi.1013423. eCollection 2025 Sep.

Improving drug-induced liver injury prediction using graph neural networks with augmented graph features from molecular optimisation.利用具有分子优化增强图特征的图神经网络改善药物性肝损伤预测。

J Cheminform. 2025 Aug 18;17(1):124. doi: 10.1186/s13321-025-01068-3.

Systematic analysis of hepatotoxicity: combining literature mining and AI language models.肝毒性的系统分析：结合文献挖掘与人工智能语言模型

Front Artif Intell. 2025 Jul 21;8:1561292. doi: 10.3389/frai.2025.1561292. eCollection 2025.

Genomics-informed drug-repurposing strategy identifies two therapeutic targets for preventing liver disease associated with metabolic dysfunction.基于基因组学的药物重新利用策略确定了两个预防与代谢功能障碍相关肝病的治疗靶点。

Am J Hum Genet. 2025 Aug 7;112(8):1778-1791. doi: 10.1016/j.ajhg.2025.06.014.

Recent advances in AI-based toxicity prediction for drug discovery.基于人工智能的药物发现毒性预测的最新进展。

Front Chem. 2025 Jul 8;13:1632046. doi: 10.3389/fchem.2025.1632046. eCollection 2025.

Impact of halogenation on scaffold toxicity assessed using HD-GEM machine learning model.使用HD-GEM机器学习模型评估卤化对支架毒性的影响。

Brief Bioinform. 2025 Jul 2;26(4). doi: 10.1093/bib/bbaf347.

Bioengineering of novel organotypic 3D human liver tissue model for drug-induced liver injury and toxicity studies.用于药物性肝损伤和毒性研究的新型器官型三维人体肝脏组织模型的生物工程

Front Toxicol. 2025 Jun 12;7:1574387. doi: 10.3389/ftox.2025.1574387. eCollection 2025.

Development of an AI model for DILI-level prediction using liver organoid brightfield images.利用肝类器官明场图像开发用于药物性肝损伤水平预测的人工智能模型。

Commun Biol. 2025 Jun 7;8(1):886. doi: 10.1038/s42003-025-08205-6.

Comprehensive analysis of high-throughput transcriptomics to distinguish drug-induced liver injury (DILI) phenotypes.通过高通量转录组学进行综合分析以区分药物性肝损伤（DILI）表型。

Arch Toxicol. 2025 Jun 4. doi: 10.1007/s00204-025-04089-x.

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

DILIrank: the largest reference drug list ranked by the risk for developing drug-induced liver injury in humans.

作者信息

机构信息

出版信息

相似文献

引用本文的文献

文献检索

文件翻译

深度研究

Suppr 超能文献

相似文献

引用本文的文献