A systems approach for analysis of high content screening assay data with topic modeling

BMC Bioinformatics

Volumn 14, Issue SUPPL.14, 2013, Pages

  Bisgin, Halil ^a   Chen, Minjun ^a   Wang, Yuping ^a   Kelly, Reagan ^a   Fang, Hong ^a   Xu, Xiaowei ^a,b   Tong, Weida ^a  

^a NATIONAL CENTER FOR TOXICOLOGICAL RESEARCH   (United States)

^b 2801 S University Ave ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DNA FRAGMENTATION; HIDDEN KNOWLEDGE; HIGH-CONTENT SCREENING; IN-VIVO EXPERIMENTS; LATENT DIRICHLET ALLOCATIONS; MULTIPLE MEASUREMENTS; TOXICITY ASSESSMENT; WORD FREQUENCIES;

ASSAYS; CELL DEATH; STATISTICS; TOOLS;

DATA MINING;

ANIMAL; APOPTOSIS; ARTICLE; CELL CULTURE; DATA MINING; DNA DAMAGE; DRUG EFFECT; GENETIC DATABASE; GENETICS; HIGH THROUGHPUT SCREENING; LIVER CELL; LYSOSOME; MALE; METABOLISM; METHODOLOGY; MITOCHONDRION; NECROSIS; RAT; SPRAGUE DAWLEY RAT; TOXICOGENETICS; DRUG EFFECTS; PROCEDURES;

ANIMALS; APOPTOSIS; CELLS, CULTURED; DATA MINING; DATABASES, GENETIC; DNA DAMAGE; HEPATOCYTES; HIGH-THROUGHPUT SCREENING ASSAYS; LYSOSOMES; MALE; MITOCHONDRIA; NECROSIS; RATS; RATS, SPRAGUE-DAWLEY; TOXICOGENETICS;

EID: 84885364503     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-14-S14-S11     Document Type: Article

References (41)

1. Watkins PB. Drug safety sciences and the bottleneck in drug development. Clin Pharmacol Ther 2011, 89(6):788-790. 10.1038/clpt.2011.63, 21593756.
2. 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 discovery today 2011, 16(15-16):697-703. 10.1016/j.drudis.2011.05.007, 21624500.
3. O'Brien PJ, Irwin W, Diaz D, Howard-Cofield E, Krejsa CM, Slaughter MR, Gao B, Kaludercic N, Angeline A, Bernardi P, et al. High concordance of drug-induced human hepatotoxicity with in vitro cytotoxicity measured in a novel cell-based model using high content screening. Arch Toxicol 2006, 80(9):580-604. 10.1007/s00204-006-0091-3, 16598496.
4. Giuliano KA, Chen YT, Taylor DL. High-content screening with siRNA optimizes a cell biological approach to drug discovery: defining the role of P53 activation in the cellular response to anticancer drugs. J Biomol Screen 2004, 9(7):557-568. 10.1177/1087057104265387, 15475475.
5. Vogt A, Tamewitz A, Skoko J, Sikorski RP, Giuliano KA, Lazo JS. The benzo[c]phenanthridine alkaloid, sanguinarine, is a selective, cell-active inhibitor of mitogen-activated protein kinase phosphatase-1. J Biol Chem 2005, 280(19):19078-19086. 10.1074/jbc.M501467200, 15753082.
6. Perlman ZE, Slack MD, Feng Y, Mitchison TJ, Wu LF, Altschuler SJ. Multidimensional drug profiling by automated microscopy. Science 2004, 306(5699):1194-1198. 10.1126/science.1100709, 15539606.
7. Tanaka M, Bateman R, Rauh D, Vaisberg E, Ramachandani S, Zhang C, Hansen KC, Burlingame AL, Trautman JK, Shokat KM, et al. An unbiased cell morphology-based screen for new, biologically active small molecules. PLoS Biol 2005, 3(5):e128. 10.1371/journal.pbio.0030128, 1073692, 15799708.
8. Lovborg H, Nygren P, Larsson R. Multiparametric evaluation of apoptosis: effects of standard cytotoxic agents and the cyanoguanidine CHS 828. Mol Cancer Ther 2004, 3(5):521-526.
9. Ghosh RN, Grove L, Lapets O. A Quantitative Cell-Based High-Content Screening Assay for the Epidermal Growth Factor Receptor-Specific Activation of Mitogen-Activated Protein Kinase. Assay and Drug Development Technologies 2004, 2(5):473-481. 10.1089/adt.2004.2.473, 15671645.
10. Milligan G. High-content assays for ligand regulation of G-protein-coupled receptors. Drug discovery today 2003, 8(13):579-585. 10.1016/S1359-6446(03)02738-7, 12850333.
11. Abraham VC, B Samson OL, Haskins JR. Automated Classification of Individual Cellular Responses Across Multiple Targets. Preclinica 2004, 2:349-355.
12. Taylor DL, Giuliano KA. Multiplexed high content screening assays create a systems cell biology approach to drug discovery. Drug Discovery Today: Technologies 2005, 2(2):149-154. 10.1016/j.ddtec.2005.05.023, 23570162.
13. Abraham VC, Taylor DL, Haskins JR. High content screening applied to large-scale cell biology. Trends in Biotechnology 2004, 22(1):15-22.
14. Xu JJ, Henstock PV, Dunn MC, Smith AR, Chabot JR, de Graaf D. Cellular Imaging Predictions of Clinical Drug-Induced Liver Injury. Toxicological Sciences 2008, 105(1):97-105. 10.1093/toxsci/kfn109, 18524759.
15. Chen M, Zhang J, Wang Y, Liu Z, Kelly R, Zhou G, Fang H, Borlak J, Tong W. Liver Toxicity Knowledge Base (LTKB) - A Systems Approach to a Complex Endpoint. Clinical Pharmacology & Therapeutics 2013, 95(5):409-412.
16. Blei DM, Ng AY, Jordan MI. Latent Dirichlet allocation. Journal of Machine Learning Research 2003, 3(4-5):993-1022.
17. Bisgin H, Liu Z, Fang H, Xu X, Tong W. Mining FDA drug labels using an unsupervised learning technique--topic modeling. BMC Bioinformatics 2011, 12(Suppl 10):S11. 10.1186/1471-2105-12-S10-S11, 3236833, 22166012.
18. Chen Y, Yin X, Li Z, Hu X, Huang JX. A LDA-based approach to promoting ranking diversity for genomics information retrieval. BMC genomics 2012, 13(Suppl 3):S2. 3394425, 22759611.
19. Zheng B, McLean DC, Lu X. Identifying biological concepts from a protein-related corpus with a probabilistic topic model. BMC Bioinformatics 2006, 7:58. 10.1186/1471-2105-7-58, 1420333, 16466569.
20. Bisgin H, Liu Z, Kelly R, Fang H, Xu X, Tong W. Investigating drug repositioning opportunities in FDA drug labels through topic modeling. BMC Bioinformatics 2012, 13(Suppl 15):S6. 10.1186/1471-2105-13-S15-S6, 3439728, 23046522.
21. He B, Tang J, Ding Y, Wang H, Sun Y, Shin JH, Chen B, Moorthy G, Qiu J, Desai P, et al. Mining Relational Paths in Integrated Biomedical Data. PLoS ONE 2011, 6(12):e27506. 10.1371/journal.pone.0027506, 3232205, 22162991.
22. Wang H, Ding Y, Tang J, Dong X, He B, Qiu J, Wild DJ. Finding Complex Biological Relationships in Recent PubMed Articles Using Bio-LDA. PLoS ONE 2011, 6(3):e17243. 10.1371/journal.pone.0017243, 3063155, 21448266.
23. Giuliano KA, Gough AH, Taylor DL, Vernetti LA, Johnston PA. Early safety assessment using cellular systems biology yields insights into mechanisms of action. J Biomol Screen 2010, 15(7):783-797. 10.1177/1087057110376413, 20639501.
24. Berry N, Barritt GJ, Edwards AM. Isolated Hepatocytes: Preparation, Properties and Applications. Elsevier Science 1991,
25. 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(2):218-227. 10.1002/mnfr.200900169, 20041446.
26. Chen M, Zhang M, Borlak J, Tong W. A Decade of Toxicogenomic Research and Its Contribution to Toxicological Science. Toxicol Sci 2012, 130(2):217-228. 10.1093/toxsci/kfs223, 22790972.
27. Kodratoff Y, Catlett J. On changing continuous attributes into ordered discrete attributes. Machine Learning â€" EWSL-91 1991, 482:164-178. Springer Berlin Heidelberg, 10.1007/BFb0017012, 3749114, 23991033.
28. Hofmann T. Probabilistic Latent Semantic Indexing. Proceedings of the Twenty-Second Annual International SIGIR Conference on Research and Development in Information Retrieval (SIGIR-99) 1999 1999, 50-57. Berkley, CA USA.
29. Deerwester S, Dumais S, Furnas G, Landauer T, Harshman R. Indexing by latent semantic analysis. Journal of the American Society for Information Science: 1990 1990, 391-407.
30. Griffiths TL, Steyvers M. Finding scientific topics. Proc Natl Acad Sci USA 2004, 101(Suppl 1):5228-5235. 387300, 14872004.
31. http://www.cs.princeton.edu/~blei/lda-c/index.html
32. Flaherty P, Giaever G, Kumm J, Jordan MI, Arkin AP. A latent variable model for chemogenomic profiling. Bioinformatics 2005, 21(15):3286-3293. 10.1093/bioinformatics/bti515, 15919724.
33. Liu B, Liu L, Tsykin A, Goodall GJ, Green JE, Zhu M, Kim CH, Li J. Identifying functional miRNA-mRNA regulatory modules with correspondence latent dirichlet allocation. Bioinformatics 2010, 26(24):3105-3111. 10.1093/bioinformatics/btq576, 2995118, 20956247.
34. Didenko VV, Ngo H, Baskin DS. Early necrotic DNA degradation: presence of blunt-ended DNA breaks, 3' and 5' overhangs in apoptosis, but only 5' overhangs in early necrosis. Am J Pathol 2003, 162(5):1571-1578. 10.1016/S0002-9440(10)64291-5, 1851179, 12707041.
35. Zong WX, Thompson CB. Necrotic death as a cell fate. Genes Dev 2006, 20(1):1-15. 10.1101/gad.1376506, 16391229.
36. Lemasters JJ, Nieminen AL, Qian T, Trost LC, Elmore SP, Nishimura Y, Crowe RA, Cascio WE, Bradham CA, Brenner DA, et al. The mitochondrial permeability transition in cell death: a common mechanism in necrosis, apoptosis and autophagy. Biochim Biophys Acta 1998, 1366(1-2):177-196. 10.1016/S0005-2728(98)00112-1, 9714796.
37. Edinger AL, Thompson CB. Death by design: apoptosis, necrosis and autophagy. Curr Opin Cell Biol 2004, 16(6):663-669. 10.1016/j.ceb.2004.09.011, 15530778.
38. Michalopoulos G, Cianciulli HD, Novotny AR, Kligerman AD, Strom SC, Jirtle RL. Liver regeneration studies with rat hepatocytes in primary culture. Cancer Res 1982, 42(11):4673-4682.
39. Cohen-Fix O. Cell biology: Import and nuclear size. Nature 2010, 468(7323):513-516. 10.1038/468513a, 3470449, 21107417.
40. Gregory T. Genome Size Evolution in Animals. 2005, 1. London: Elsevier Academic Press.
41. Miyaoka Y, Ebato K, Kato H, Arakawa S, Shimizu S, Miyajima A. Hypertrophy and Unconventional Cell Division of Hepatocytes Underlie Liver Regeneration. Current Biology 2012, 22(13):1166-1175. 10.1016/j.cub.2012.05.016, 22658593.