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LiverTox: Clinical and Research Information on Drug-Induced Liver Injury [Internet]. Bethesda (MD): National Institute of Diabetes and Digestive and Kidney Diseases; 2012-.

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LiverTox: Clinical and Research Information on Drug-Induced Liver Injury [Internet].

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Last Update: May 3, 2019.

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Other Relevant Hepatotoxicity Databases And Projects

  • Fourches D, Barnes JC, Day NC, Bradley P, Reed JZ, Tropsha A. Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species. Chem Res Toxicol. 2010;23:171–83. [PMC free article: PMC2850112] [PubMed: 20014752]
  • Liu Z, Shi Q, Ding D, Kelly R, Fang H, Tong W. Translating clinical findings into knowledge in drug safety evaluation--drug induced liver injury prediction system (DILIps). PLoS Comput Biol. 2011:7. [PMC free article: PMC3240589] [PubMed: 22194678]
  • Low Y, Uehara T, Minowa Y, Yamada H, Ohno Y, Urushidani T, Sedykh A, Muratov E, Kuz'min V, Fourches D, Zhu H, Rusyn I, Tropsha A. Predicting drug-induced hepatotoxicity using QSAR and toxicogenomics approaches. Chem Res Toxicol. 2011;24:1251–62. [PMC free article: PMC4281093] [PubMed: 21699217]
  • Myshkin E, Brennan R, Khasanova T, Sitnik T, Serebriyskaya T, Litvinova E, Guryanov A, et al. Prediction of organ toxicity endpoints by QSAR modeling based on precise chemical-histopathology annotations. Chem Biol Drug Des. 2012;80:406–16. [PubMed: 22583392]
  • Przybylak KR, Cronin MT. In silico models for drug-induced liver injury--current status. Expert Opin Drug Metab Toxicol. 2012;8:201–17. [PubMed: 22248266]
  • Zhang M, Chen M, Tong W. Is toxicogenomics a more reliable and sensitive biomarker than conventional indicators from rats to predict drug-induced liver injury in humans? Chem Res Toxicol. 2012;25:122–9. [PubMed: 22122743]
  • Chen M, Hong H, Fang H, Kelly R, Zhou G, Borlak J, Tong W. 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. Toxicol Sci. 2013;136:242–9. [PubMed: 23997115]
  • Davis AP, Murphy CG, Johnson R, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, et al. The Comparative Toxicogenomics Database: update 2013. Nucleic Acids Res. 2013;41 http://ctdbase​.org/detail​.go?type=disease&acc=MESH​%3AD056486 [PMC free article: PMC3531134] [PubMed: 23093600]
  • Rodgers AD, Zhu H, Fourches D, Rusyn I, Tropsha A. Modeling liver-related adverse effects of drugs using knearest neighbor quantitative structure-activity relationship method. Chem Res Toxicol. 2010;23:724–32. [PMC free article: PMC2965736] [PubMed: 20192250]
  • Xing L, Wu L, Liu Y, Ai N, Lu X, Fan X. LTMap: a web server for assessing the potential liver toxicity by genome-wide transcriptional expression data. J Appl Toxicol. 2013 [PubMed: 24022982]
  • Zhang JD, Berntenis N, Roth A, Ebeling M. Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity. Pharmacogenomics J. 2013 [PMC free article: PMC4034126] [PubMed: 24217556]
  • Shoda LK, Woodhead JL, Siler SQ, Watkins PB, Howell BA. Linking physiology to toxicity using DILIsym®, a mechanistic mathematical model of drug-induced liver injury. Biopharm Drug Dispos. 2014;35:33–49. [PubMed: 24214486]
  • Zhu XW, Sedykh A, Liu SS. Hybrid in silico models for drug-induced liver injury using chemical descriptors and in vitro cell-imaging information. J Appl Toxicol. 2014;34:281–8. [PubMed: 23640866]

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