Drug-induced liver injury classification model based on in vitro human transcriptomics and in vivo rat clinical chemistry data

References

• Chen M, Vijay V, Shi Q, Liu Z, Fang H, Tong W. FDA-approved drug labeling for the study of drug-induced liver injury. Drug Discov Today 2011; 16:697-703; PMID:21624500; http://dx.doi.org/10.1016/j.drudis.2011.05.007
   PubMed Web of Science ®Google Scholar
• 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; PMID:22122743; http://dx.doi.org/10.1021/tx200320e
   PubMed Web of Science ®Google Scholar
• Blomme EA, Yang Y, Waring JF. Use of toxicogenomics to understand mechanisms of drug-induced hepatotoxicity during drug discovery and development. Toxicol Lett 2009; 186:22-31; PMID:18996174; http://dx.doi.org/10.1016/j.toxlet.2008.09.017
   PubMed Web of Science ®Google Scholar
• Natsoulis G, Pearson CI, Gollub J, P Eynon B, Ferng J, Nair R, Idury R, Lee MD, Fielden MR, Brennan RJ, et al. The liver pharmacological and xenobiotic gene response repertoire. Mol Syst Biol 2008; 4:175; PMID:18364709; http://dx.doi.org/10.1038/msb.2008.9
   PubMed Web of Science ®Google Scholar
• Nie AY, McMillian M, Parker JB, Leone A, Bryant S, Yieh L, Bittner A, Nelson J, Carmen A, Wan J, et al. Predictive toxicogenomics approaches reveal underlying molecular mechanisms of nongenotoxic carcinogenicity. Mol Carcinog 2006; 45:914-33; PMID:16921489; http://dx.doi.org/10.1002/mc.20205
   PubMed Web of Science ®Google Scholar
• CAMDA. 2012. http://camda.bioinfo.cipf.es/camda2012/
   Google Scholar
• Uehara T, Ono A, Maruyama T, Kato I, Yamada H, Ohno Y, Urushidani T. The Japanese toxicogenomics project: application of toxicogenomics. Mol Nutr Food Res 2010; 54:218-27; PMID:20041446; http://dx.doi.org/10.1002/mnfr.200900169
   PubMed Web of Science ®Google Scholar
• CAMDA. 2013. http://dokuwiki.bioinf.jku.at/doku.php
   Google Scholar
• Magkoufopoulou C, Claessen SM, Tsamou M, Jennen DG, Kleinjans JC, van Delft JH. A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo. Carcinogenesis 2012; 33:1421-9; PMID:22623647; http://dx.doi.org/10.1093/carcin/bgs182
   PubMed Web of Science ®Google Scholar
• Tibshirani R, Hastie T, Narasimhan B, Chu G. Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc Natl Acad Sci U S A 2002; 99:6567-72; PMID:12011421; http://dx.doi.org/10.1073/pnas.082099299
   PubMed Web of Science ®Google Scholar
• Dobbin KK, Simon RM. Optimally splitting cases for training and testing high dimensional classifiers. BMC Med Genomics 2011; 4:31; PMID:21477282; http://dx.doi.org/10.1186/1755-8794-4-31
   PubMed Web of Science ®Google Scholar
• 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; PMID:23997115; http://dx.doi.org/10.1093/toxsci/kft189
   PubMed Web of Science ®Google Scholar
• Jennen D, Polman J, Bessem M, Coonen M, Caiment F, Hebels D, et al. DILI classification model based on in vitro human transcriptomics and in vivo rat clinical chemistry data. CAMDA challange 2013; http://dokuwiki.bioinf.jku.at/lib/exe/fetch.php/jennen.pdf
   Google Scholar
• Giannini EG, Testa R, Savarino V. Liver enzyme alteration: a guide for clinicians. CMAJ 2005; 172:367-79; PMID:15684121; http://dx.doi.org/10.1503/cmaj.1040752
   PubMed Web of Science ®Google Scholar
• Tsubouchi H, Ido A, Mawatari S. New Development in Treating Liver Disorders: Approaches to liver function test from mild to fulminant disorders. Japan Medical Association Journal 2010; 53:218-23.
   Google Scholar
• Fleuren WW, Verhoeven S, Frijters R, Heupers B, Polman J, van Schaik R, de Vlieg J, Alkema W. CoPub update: CoPub 5.0 a text mining system to answer biological questions. Nucleic Acids Res 2011; 39:W450-4; PMID:21622961; http://dx.doi.org/10.1093/nar/gkr310
   PubMed Web of Science ®Google Scholar
• MetaCore. http://thomsonreuters.com/metacore/
   Google Scholar
• Dennis G Jr., Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA. DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biol 2003; 4:3; PMID:12734009; http://dx.doi.org/10.1186/gb-2003-4-5-p3
   PubMed Web of Science ®Google Scholar
• Smoot ME, Ono K, Ruscheinski J, Wang PL, Ideker T. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 2011; 27:431-2; PMID:21149340; http://dx.doi.org/10.1093/bioinfor-matics/btq675
   PubMed Web of Science ®Google Scholar
• Kotsiantis S, Kanellopoulos D, Pintelas P. Handling imbalanced datasets: A review. GESTS International Transactions on Computer Science and Engineering 2006; 30:25-36.
   Google Scholar
• Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP. SMOTE: Synthetic Minority Over-sampling Technique. J Artif Intell Res 2002; 16:321-57.
   Web of Science ®Google Scholar
• Livyatan I, Meshorer E. The HDAC interaction network. Mol Syst Biol 2013; 9:671; PMID:23752267; http://dx.doi.org/10.1038/msb.2013.33.
   PubMed Web of Science ®Google Scholar
• Barneda-Zahonero B, Parra M. Histone deacetylases and cancer. Mol Oncol 2012; 6:579-89; PMID:22963873; http://dx.doi.org/10.1016/j.molonc.2012.07.003
   PubMed Web of Science ®Google Scholar
• Wang Y, Hu Y, Chao C, Yuksel M, Colle I, Flavell RA, Ma Y, Yan H, Wen L. Role of IRAK-M in alcohol induced liver injury. PLoS One 2013; 8:e57085; PMID:23437317; http://dx.doi.org/10.1371/journal.pone.0057085
   PubMedGoogle Scholar
• Li S, Ogawa W, Emi A, Hayashi K, Senga Y, Nomura K, Hara K, Yu D, Kasuga M. Role of S6K1 in regulation of SREBP1c expression in the liver. Biochem Biophys Res Commun 2011; 412:197-202; PMID:21806970; http://dx.doi.org/10.1016/j.bbrc.2011.07.038
   PubMed Web of Science ®Google Scholar
• Nam CW, Park NH, Park BR, Shin JW, Jung SW, Na YW, Seo JH. Mitotic checkpoint gene MAD1 in hepatocellular carcinoma is associated with tumor recurrence after surgical resection. J Surg Oncol 2008; 97:567-71; PMID:18491369; http://dx.doi.org/10.1002/jso.20999
   PubMed Web of Science ®Google Scholar
• Sze KM, Ching YP, Jin DY, Ng IO. Role of a novel splice variant of mitotic arrest deficient 1 (MAD1), MAD1beta, in mitotic checkpoint control in liver cancer. Cancer Res 2008; 68:9194-201; PMID:19010891; http://dx.doi.org/10.1158/0008-5472.CAN-08-2600
   PubMed Web of Science ®Google Scholar
• Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 2003; 4:249-64; PMID:12925520; http://dx.doi.org/10.1093/biostatistics/4.2.249
   PubMed Web of Science ®Google Scholar
• Dai M, Wang P, Boyd AD, Kostov G, Athey B, Jones EG, Bunney WE, Myers RM, Speed TP, Akil H, et al. Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data. Nucleic Acids Res 2005; 33:e175; PMID:16284200; http://dx.doi.org/10.1093/nar/gni179
   PubMed Web of Science ®Google Scholar
• Eijssen LM, Jaillard M, Adriaens ME, Gaj S, de Groot PJ, Müller M, Evelo CT. User-friendly solutions for microarray quality control and pre-processing on ArrayAnalysis.org. Nucleic Acids Res 2013; 41:W71-6; PMID:23620278; http://dx.doi.org/10.1093/nar/gkt293
   PubMed Web of Science ®Google Scholar