Generating 'omic knowledge': The role of informatics in high content screening

Combinatorial Chemistry and High Throughput Screening

Volumn 12, Issue 9, 2009, Pages 917-925

  Collins, Mark A ^a  

^a Thermo Fisher Scientific   (United States)

Author keywords

Bioinformatics; Drug discovery; Genomics; HCA; HCS; High content analysis; High content screening; Informatics; Ontology; Systems biology

Indexed keywords

AUTOMATION; BIOENGINEERING; BIOINFORMATICS; COMPUTER MODEL; GENOME; HIGH THROUGHPUT SCREENING; IMAGE ANALYSIS; INFORMATION PROCESSING; PHENOTYPE; PRIORITY JOURNAL; QUALITY CONTROL; REVIEW;

COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; HIGH-THROUGHPUT SCREENING ASSAYS; HUMANS; INFORMATICS; TISSUE ARRAY ANALYSIS;

EID: 70349439132     PISSN: 13862073     EISSN: None     Source Type: Journal    
DOI: 10.2174/138620709789383259     Document Type: Review

References (43)

1. http://www.ornl.gov/sci/techresources/Human-Genome/project/about.shtml
2. Dunlay, T.; Czekalski, W.; and Collins, M. Overview of Informatics for HCS. Methods Mol. Biol., 2006, 356, 269-280.
3. Brazma, A.; Hingamp, P.; Quackenbush, J.; Sherlock, G.; Spellman, P.; Stoeckert, C.; Aach, J.; Ansorge, W.; Ball, C.A.; Causton, H.C.; Gaasterland, T.; Glenisson, P.; Holstege, F.C.; Kim, I.F.; Markowitz, V.; Matese, J.C.; Parkinson, H.; Robinson, A.; Sarkans, U.; Schulze-Kremer, S.; Stewart, J.; Taylor, R.; Vilo, J.; Vingron, M. Minimum Information about a microarray experiment (MIAME),- toward standards for microarray data. Nat. Genet, 2001, 29, 365-371. (Pubitemid 34326681)
4. Taylor, C.F.; Paton, N.W.; Lilley, K.S.; Binz, P.A.; Julian, R.K. Jr.; Jones, A.R.; Zhu, W.; Apweiler, R.; Aebersold, R.; Deutsch, E.W.; Dunn, M.J.; Heck, A.J.; Leitner, A.; Macht, M.; Mann, M.; Martens, L.; Neubert, T.A.; Patterson, S.D.; Ping, P.; Seymour, S.L.; Souda, P.; Tsugita, A.; Vandekerckhove, J.; Vondriska, T.M.; Whitelegge, J.P.; Wilkins, M.R.; Xenarios, I.; Yates, J.R. 3rd., Hermjakob, H. The minimum information about a proteomics experiment (MIAPE). Nat. Biotechnol., 2007, 25, 887-893.
5. Wiemann, S.; Mehrle, A.; Hahne, F.; Hermjakob, H.; Apweiler2, R.; Arlt, D.; Bechtel, S.; Bielke, W.; Birmingham, A.; Boese, O.; Bork, P.; Buchholz, F.; Cai, X.; Camon, E.; Carninci, P.; Chanda, S.K.; Chen, Z.; Cusick, M.; Echeverri, C.; Eils, J.; Eils, R.; Frank, R.; Fraser, A.; Girod, A.; Haedrich, B.; Hannus, M.; Harris, M.; Hayashizaki, Y.; Hide, W.; Hofmann, O.; Huber, P.; Hyman, A.; Jensen, L.; Kallioniemi, O.; Khvorova, A.; Koski, L.; Kraybill, B.; LaBaer, J.; Landegren, U.; Lawerenz, C.; Lehrach, H.; Liu, F.F.; Majety, M.; Prevot, B.M.; Mills, G.B.; Nomura, N.; the OBI working group, Perrimon, N.; Pizarro, A.; Poustka, A.; Quackenbush, J.; Rosenfelder, H.; Sahin, O.; Ashtiani, K.S.; Sasse, F.; Sauermann, M.; Schimmer, A.D.; Schmidt, C.; Selfors, L.; Shamu, C.; Sönnichsen, B.; Taylor, C.; Temple, G.; Vidal, M.; Wrobel, D.J. MIACA - minimum information about a cellular assay, and the cellular assay object model . Submitted to Nat. Biotechnol., 2007, for review http://www.nature.com/nbt/ consult/index.html
6. Goldberg, I.G.; Allan, C.; Burel, J.M.; Creager, D.; Falconi, A.; Hochheiser, H.; Johnston, J.; Mellen, J.; Sorger, P.K.; Swedlow, J.R. The Open Microscopy Environment (OME) Data Model and XML File: Open tools for informatics and quantitative analysis in biological imaging. Genome Biol., 2005, 6, R47.
7. Dean, P.N.; Bagwell, C.B.; Lindmo, T.; Murphy, R.F.; Salzman, G.C. Data file standard for flow cytometry. Cytometry, 1990, 11, 323-332.
8. http://wiki.ficcs.org/ficcs/MIFlowCyt
9. SBS. - report from the data analysis Special Interest Group, 2008.
10. Smith, B. The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat. Biotechnol., 2007, 25, 1251-1255. (Pubitemid 350076511)
11. Ainscow, E. 2007 Statistical techniques for handling high content screening data. Eur. Pharm. Rev., 2007, 5, 30-37.
12. Malo, N.; Hanley, J.A.; Cerquozzi, S.; Pelletier, J.; Nadon, R. Statistical practice in high throughput screening data analysis. Nat. Biotechnol., 2006, 24, 167-175. (Pubitemid 43221699)
13. Breiman, L.; Friedman, J.; Olshen, R.A.; Stone, C.J. Classification and regression trees. Wadsworth, 1984, pp. 78-107.
14. Abraham, V.; Samson, B.; Lapets, O.; Haskins, J.R. Automated classification of individual cellular responses across multiple targets. Preclinica, 2004, 2, 349-355.
15. Tanaka, M.; Bateman, R.; Rauh, D.; Vaisberg, E.; Ramachandani, S.; Zhang, C.; Hansen, K.C.; Burlingame, A.L.; Trautman, J.K.; Shokat, K.M.; Adams, C.L. An unbiased cell morphology-based screen for new, biologically active small molecules. PLoS Biol., 2005, 3(5), e128.
16. Chakravarti, J.M.; Laha, R.G.; Roy, J. Handbook of Methods of Applied Statistics, John Wiley and Sons, 1967, vol. 1, pp. 392-394.
17. Giuliano, K.A.; Cheung, W.S.; Curran, D.P.; Day, B.W.; Kassick, A.J.; Lazo, J.S.; Nelson, S.G.; Shin, Y.; Taylor, D.L. Systems cell biology knowledge created from high content screening. Assay Drug Dev. Technol., 2005, 3(5), 501-514.
18. Perlman, Z.E.; Slack, M.D.; Feng, Y.; Mitchison, T.J.; Wu, L.F.; Altschuler, S.J. Multidimensional drug profiling by automated microscopy. Science, 2004, 306 (5699), 1194.
19. Giuliano, K.A. A high content profiling of drug-drug interactions: cellular targets involved in the modulation of microtubule drug action by the antifungal ketoconazole. J. Biomol. Screen., 2003, 8, 125-135. (Pubitemid 40503615)
20. Tencza, S.B.; Sipe, M.A. Detection and classification of threat agents via high content assays of mammalian cells. J. Appl. Toxicol., 2004, 24, 371-377.
21. Giuliano, K.; Chen, Y.; Taylor, L. 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. (Pubitemid 40503514)
22. Durr, O.; Duval, F.; Nichols, A.; Lang, P.; Brodte, A.; Heyse, S.; Besson, D. Robust hit identification by quality assurance and multivariate data analysis of a high content, cell-based assay. J. Biomol. Screen., 2007, 12, 1042-1049. (Pubitemid 350179703)
23. Tao, C.Y., Hoyt, J.; Feng, Y. A support vector machine classifier for recognizing mitotic subphases using high content screening data. J. Biomol. Screen., 2007, 12, 490-496. (Pubitemid 46871833)
24. Vapnik, V. The Nature of Statistical Learning Theory. Springer-Verlag, 1995.
25. Tao, C.Y.; Hoyt, J.; Feng, Y. A support vector machine classifier for recognizing mitotic subphases using high content screening data. J. Biomol. Screen., 2007, 12(4), 490-496. (Pubitemid 46871833)
26. Low, J.; Stancato. L.; Lee, J.; Sutherland, J.J. Prioritizing hits from phenotypic high content screens Curr. Opin. Drug Discov. Dev., 2008, 11(3), 338-345.
27. Björklund, M.; Taipale, M.; Varjosalo, M.; Saharinen, J.; Lahdenperä, J.; Taipale, J. Identification of pathways regulating cell size and cell-cycle progression by RNAi. Nature, 2006, 439:1009-1013. (Pubitemid 43292422)
28. Li, Y.; Pan, J.; Li, J.L.; Lee, J.H.; Tunkey, C.; Saraf, K.; Garbe, J.C.; Whitley, M.Z.; Jelinsky, S.A.; Stampfer, M.R.; Haney, S.A. Transcriptional changes associated with breast cancer occur as normal human mammary epithelial cells overcome senescence barriers and become immortalized. Mol. Cancer, 2007, 6, 7.
29. Lotharius, J.; Falsig, J.; van Beek, J.; Payne, S.; Dringen, R.; Brundin, P.; Leist, M. Progressive degeneration of human mesencephalic neuron-derived cells triggered by dopamine-dependent oxidative stress is dependent on the mixed-lineage kinase pathway. J. Neurosci., 2005, 25(27), 6329-6342. (Pubitemid 40962528)
30. Liu, L.; Cao, Y.; Chen, C.; Zhang, X.; McNabola, A.; Wilkie, D.; Wilhelm, S.; Lynch, M.; Carter, C. Sorafenib blocks the RAF/MEK/ERK pathway, inhibits tumor angiogenesis, and induces tumor cell apoptosis in hepatocellular carcinoma model PLC/PRF/5. Cancer Res., 2006, 66, 11851-11858. (Pubitemid 46094197)
31. Wang, K.; Li, M.; Bucan, M. Pathway-based approaches for analysis of genomewide association studies. Am. J. Hum. Genet., 2007, 81(6), 1278-1283. (Pubitemid 350211456)
32. Lohl, S.H.; Francescut, L.; Lingor, P.; Bähr M.; Nicotera, P. Identification of new kinase clusters required for neurite outgrowth and retraction by a loss-of-function RNA interference screen. Cell Death Differ., 2008, 15, 283-298.
33. The National Resource for Cell Analysis and Modeling (NRCAM) is a national resource center supported by the National Center for Research Resources (NCRR), at the National Institutes of Health (NIH).http://www.nrcam.uchc.edu/ index.html
34. KEGG: Kyoto Encyclopedia of Genes and Genomes http://www.genome.jp/kegg/
35. Brown, S-A.; Morgan, F.; Watras, J.; Loew, L.M. Analysis of phosphatidylinositol-4,5-bisphosphate signaling in cerebellar purkinje spines. Biophys. J., 2008, 95, 1795-1812.
36. Neves, S.R.; Tsokas, P.; Sarkar, A.; Grace, E.A.; Rangamani, P.; Taubenfeld, S.M.; Alberini, C.M.; Schaff, J.C.; Blitzer, R.D.; Moraru, I.I.; Iyengar, R. Cell shape and negative links in regulatory motifs together control spatial information flow in signaling networks. Cell, 2008, 133, 666-680. (Pubitemid 351636307)
37. Duman, J.G.; Chen, L.; Hille, B. Calcium transport mechanisms of PC12 cells. J. Gen. Physiol., 2008, 131(4), 307-323
38. Zhang, J.H.; Chung, T.D.Y.; Oldenburg, K.R. A simple statistical parameter for use in evaluation and validation of high throughput screening assays. J. Biomol. Screen., 1999, 4, 67-73.
39. Xia, Z.; Zhou, X.; Yin, Z.; Sun, Y.; Wong, S.T.; Mao, Y. Automated recognition of cellular phenotypes by support vector machines with feature reduction. Int. J. Knowl.-Based Intell. Eng. Syst., 2007, 11(4), 247-253.
40. Hill, A.A.; LaPan, P.; Li, Y.; Haney, S. Impact of image segmentation on high content screening data quality for SK-BR-3 cells. BMC Bioinform., 2007, 8, 340. (Pubitemid 350131380)
41. Wang, J.; Zhou, X.; Bradley, P.L.; Chang, S.F.; Perrimon, N.; Wong, S.T. Cellular phenotype recognition for high content RNA interference genome-wide screening. J. Biomol. Screen., 2008, 13(1), 29-39.
42. Young, D.W.; Bender, A.; Hoyt, J.; McWhinnie, E.; Chirn, G.W.; Tao, C.Y.; Tallarico, J.A.; Labow, M.; Jenkins, J.L.; Mitchison, T.J.; Feng, Y. Integrating high content screening and ligand-target prediction to identify mechanism of action. Nat. Chem. Biol., 2008, 4, 59-68. (Pubitemid 350273652)
43. Wong, S.T.C. Bioinformatics of high content screening. Screen. - Trends Drug Discov., 2006, 1, 18.