Determination of minimal transcriptional signatures of compounds for target prediction

Eurasip Journal on Bioinformatics and Systems Biology

Volumn 2012, Issue 1, 2012, Pages

  Nigsch, Florian ^a   Hutz, Janna ^b   Cornett, Ben ^b   Selinger, Douglas W ^b   McAllister, Gregory ^b   Bandyopadhyay, Somnath ^c   Loureiro, Joseph ^b   Jenkins, Jeremy L ^b  

^a NOVARTIS PHARMA AG   (Switzerland)

^b NOVARTIS INSTITUTES FOR BIOMEDICAL RESEARCH   (United States)

^c BRISTOL MYERS SQUIBB   (United States)

Author keywords

Compute unified device architecture (CUDA); Genetic algorithm; Graphics processing unit (GPU) program ming; Target prediction; Transcriptional profiling

Indexed keywords

BIOLOGICAL INTERACTIONS; BIOLOGICAL VARIABILITY; CELLULAR ASSAYS; COMPUTE UNIFIED DEVICE ARCHITECTURES; DRUG DISCOVERY; EXPRESSION DATA; EXPRESSION PROFILING; GAIN INSIGHT; GRAPHICS PROCESSING UNIT; HIGH-THROUGHPUT; MECHANISM OF ACTION; MODE OF ACTION; MOLECULAR TARGETS; OXIDATIVE PHOSPHORYLATION; PROTEIN TARGETS; TARGET PREDICTION; TRANSCRIPTIONAL PROFILING;

COMPUTER GRAPHICS; COMPUTER GRAPHICS EQUIPMENT; FORECASTING; GENETIC ALGORITHMS; PHOSPHORYLATION; PLANTS (BOTANY); PROGRAM PROCESSORS;

GENE EXPRESSION;

EQUILIN; HYDROXYSTEROID DEHYDROGENASE; STAUROSPORINE;

ARTICLE; CELL ASSAY; CELL METABOLISM; CONTROLLED STUDY; CYTOSKELETON; G2 PHASE CELL CYCLE CHECKPOINT; GENE EXPRESSION PROFILING; GENETIC ALGORITHM; GENETIC TRANSCRIPTION; HUMAN; HUMAN CELL; MALE; OXIDATIVE PHOSPHORYLATION; PROTEIN TARGETING; S PHASE CELL CYCLE CHECKPOINT; SIGNAL TRANSDUCTION;

EID: 84865464330     PISSN: 16874145     EISSN: 16874153     Source Type: Journal    
DOI: 10.1186/1687-4153-2012-2     Document Type: Article

References (26)

1. D di Bernardo, MJ Thompson, TS Gardner, SE Chobot, EL Eastwood, AP Wojtovich, SJ Elliott, SE Schaus, JJ Collins, Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks. Nat Biotech. 23(3), 377-383 (2005). doi:10.1038/nbt1075
2. M Keiser, B Roth, B Armbruster, P Ernsberger, J Irwin, B Shoichet, Relating protein pharmacology by ligand chemistry. Nat Biotechnol. 25(2), 197-206 (2007). doi:10.1038/nbt1284
3. F Nigsch, A Bender, JL Jenkins, JBO Mitchell, Ligand-target prediction using winnow and naive bayesian algorithms and the implications of overall performance statistics. J Chem Inf Model. 48(12), 2313-2325 (2008). doi:10.1021/ci800079x
4. M Campillos, M Kuhn, A Gavin, L Jensen, P Bork, Drug target identification using side-effect similarity. Science. 321(5886), 263-266 (2008). doi:10.1126/ science.1158140
5. FJ King, DW Selinger, FA Mapa, J Janes, H Wu, TR Smith, Q-Y Wang, P Niyomrattanakitand, DG Sipes, A Brinker, JA Porter, VE Myer, Pathway reporter assays reveal small molecule mechanisms of action. J Assoc Lab Autom. 14(6), 374-382 (2009). doi:10.1016/j.jala.2009.08.001
6. PE Blower, C Yang, MA Fligner, JS Verducci, L Yu, S Richman, JN Weinstein, Pharmacogenomic analysis: correlating molecular substructure classes with microarray gene expression data. Pharmacogen J. 2(4), 259-271 (2002). doi:10.1038/sj.tpj.6500116
7. J Lamb, ED Crawford, D Peck, JW Modell, IC Blat, MJ Wrobel, J Lerner, J-P Brunet, A Subramanian, KN Ross, M Reich, H Hieronymus, G Wei, SA Armstrong, SJ Haggarty, PA Clemons, R Wei, SA Carr, ES Lander, TR Golub, The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease. Science. 313(5795), 1929-1935 (2006). doi:10.1126/science.1132939
8. F Iorio, R Bosotti, E Scacheri, V Belcastro, P Mithbaokar, R Ferriero, L Murino, R Tagliaferri, N Brunetti-Pierri, A Isacchi, D di Bernardo, Discovery of drug mode of action and drug repositioning from transcriptional responses. Proc Natl Acad Sci USA. 107(33), 14621 \-14626 (2010). doi:10.1073/ pnas.1000138107
9. Affymetrix Human Genome U133 Set http://www.affymetrix.com/support/ help/faqs/hgu133/index.jsp. Accessed 06 Jan 2012
10. Panomics Luminex Assays http://www.panomics.com/index.php? id=products-luminexAssays. Accessed 06 Jan 2012
11. R Morphy, C Kay, Z Rankovic, From magic bullets to designed multiple ligands. Drug Discov Today. 9(15), 641-651 (2004). doi:10.1016/S1359-6446 (04)03163-0
12. M Iskar, M Campillos, M Kuhn, LJ Jensen, Vvan Noort, P Bork, Drug-induced regulation of target expression. PLoS Comput Biol. 6(9), e1000925 (2010). doi:10.1371/journal.pcbi.1000925
13. D Emig, T Kacprowski, M Albrecht, Measuring and analyzing tissue specificity of human genes and protein complexes. EURASIP J Bioinf Syst Biol. 2011(1), 5 (2011). doi:10.1186/1687-4153-2011-5
14. I Nobeli, AD Favia, JM Thornton, Protein promiscuity and its implications for biotechnology. Nat Biotech. 27(2), 157-167 (2009). doi:10.1038/nbt1519
15. AM Edwards, R Isserlin, GD Bader, SV Frye, TM Willson, FH Yu, Too many roads not taken. Nature. 470(7333), 163-165 (2011). doi:10.1038/470163a
16. CM Krejsa, D Horvath, SL Rogalski, JE Penzotti, B Mao, F Barbosa, JC Migeon, Predicting ADME properties and side effects: the BioPrint approach. Curr Opin Drug Discov Dev. 6(4), 470-480 (2003)
17. D Szklarczyk, A Franceschini, M Kuhn, M Simonovic, A Roth, P Minguez, T Doerks, M Stark, J Muller, P Bork, LJ Jensen, C von Mering, The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored. Nucleic Acids Res. 39(suppl 1), D561-D568 (2011)
18. D Whitley, A genetic algorithm tutorial. Stat Comput. 4(2), 65-85 (1994)
19. R Kumar, S Blakemore, C Ellis, E Petricoin, D Pratt, M Macoritto, A Matthews, J Loureiro, K Elliston, Causal reasoning identifies mechanisms of sensitivity for a novel AKT kinase inhibitor, GSK690693. BMC Genomics. 11(1), 419 (2010). doi:10.1186/1471-2164-11-419
20. R Development Core Team, R: A Language and Environment for Statistical Computing, (R Foundation for Statistical Computing, Vienna, 2011)
21. L Gautier, L Cope, BM Bolstad, RA Irizarry, Affy-analysis of Affymetrix GeneChip data at the probe level. Bioinformatics. 20(3), 307-315 (2004). doi:10.1093/bioinformatics/btg405
22. RA Irizarry, BM Bolstad, F Collin, LM Cope, B Hobbs, TP Speed, Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 31(4), e15 (2003). doi:10.1093/nar/gng015
23. A Gaulton, LJ Bellis, AP Bento, J Chambers, M Davies, A Hersey, Y Light, S McGlinchey, D Michalovich, B Al-Lazikani, JP Overington, ChEMBL: a large-scale bioactivity database for drug discovery. Nucleic Acids Res. 40, D1100-D1107 (2012). doi:10.1093/nar/gkr777
24. C Knox, V Law, T Jewison, P Liu, S Ly, A Frolkis, A Pon, K Banco, C Mak, V Neveu, Y Djoumbou, R Eisner, AC Guo, DS Wishart, DrugBank 3.0: a comprehensive resource for omics' research on drugs. Nucleic Acids Res, 39Database: D1035-D1041 (2011)
25. T Segaran, Programming Collective Intelligence: Building Smart Web 2.0 Applications, 1st edn. (O'Reilly Media, USA, 2007)
26. RK Curtis, M Oreši?, A Vidal-Puig, Pathways to the analysis of microarray data. Trends Biotechnol. 23(8), 429-435 (2005). doi:10.1016/j tibtech2005.05.011