Data Integration Systems Toxicology Toxicogenomics Toxicogenomics is the study of the response of a genome to environmental stressors and toxicants Combines genetics genomic scale mRNA expression genomics cell and tissue wide protein expression proteomics metabolite profiling metabolomics and bioinformatics with conventional toxicology in an effort to understand the role of gene environment interactions in disease Credit M Waters NIEHS A Knowledge Base Defined A knowledge base uses data and information to carry out tasks that create new information and new understanding The Chemical Effects in Biological Systems CEBS knowledge base aims to be a dynamic system for integrating large volumes of disparate information in a framework that serves as a continually changing heuristic engine CEBS will evolve both in content and capabilities to become a system of predictive toxicology http cebs niehs nih gov Credit M Waters NIEHS Systems Biology a complete description of how the components of a biological system work together Ideker Galitski Hood 2001 A new approach to decoding life systems biology Ann Rev Genomics Hum Genet 2 343 372 Describe a system Develop a better model of the system Perturb a system Measure changes globally Waters and Fostel 2004 Toxicogenomics and systems toxicology Aims and prospects Nat Rev Genet 5 936 948 Credit M Waters NIEHS Toxicogenomics Objectives Why do we need Knowledge Bases Compare toxicogenomic effects of chemicals stressors across species Yielding signatures of altered gene protein expression Phenotypically anchor these changes with conventional toxicology data Classifying effects as well as disease phenotypes Delineate global changes as adaptive pharmacologic or toxic outcomes Defining biomarkers sequence of key events mechanisms of action Credit M Waters NIEHS Contemporary Toxicology Experimental Design Chemical exposure of animal models Microarray Analysis Bioinformatics analysis Toxicological Characterization acute toxicity pathology clinical chemistry chronic toxicity carcinogenicity Identification of candidate biomarkers Data Integration Verify Biomarker Discovery Key events Mechanisms of action Proteomic Analysis Fractionation of target and non target tissues 2D PAGE MS SELDI Candidate protein identification mass spec Analysis of serum for candidate proteins Verify Credit M Waters NIEHS A Framework for Systems Toxicology Waters Fostel Nat Rev Genet 2004 Bioinformatics challenges and biological complexity Waters Fostel Nat Rev Genet 2004 Cy3 Cy5 Cy5 Cy3 Cy5 log2 Cy3 200 10000 50 00 5 64 4800 4800 1 00 0 00 9000 300 0 03 4 91 Slide courtesy of C M Perou Where does the data go NAME BC FUMI0 BC FUMI4 BC FUMI4 BC601B A BC601A B BC FUMI1 BC FUMI2 BC FUMI2 BC FUMI1 BC FUMI1 BC102B B BC FUMI2 BC FUMI3 BC FUMI3 BC FUMI1 BC FUMI1 0 242 1 21 0 253 0 841 0 423 0 363 0 852 1 383 2 642 0 501 0 25 0 605 0 636 0 229 0 626 adipose differentiation related prote 0 908 0 485 0 397 0 767 0 886 0 251 0 683 0 057 0 317 1 2 0 125 0 536 0 248 0 365 plasminogen activator urokinase re plasminogen activator urokinase re 0 4635 0 3545 0 8975 1 23 0 8335 0 0175 1 002 0 1555 0 4325 1 008 0 1785 0 7445 0 1485 0 0555 0 2055 0 551 0 151 0 422 0 007 0 638 0 087 0 689 0 91 0 853 0 052 0 492 0 201 0 152 0 368 0 741 coronin actin binding protein 1C A coatomer protein complex subun 1 061 0 8655 0 1235 0 9895 0 3815 0 4955 0 2775 0 1465 1 109 0 8635 0 2615 0 0905 0 3225 0 6035 0 0195 0 9345 coactosin like protein R78490 0 8835 0 4545 0 2375 1 177 0 2155 0 2975 0 9385 0 2815 1 494 0 5985 0 4095 0 3465 0 2185 0 1345 0 2895 0 5525 folylpolyglutamate synthase R44864 0 686 1 583 1 313 0 048 0 272 0 143 0 394 0 423 0 445 0 854 0 322 0 03 0 412 0 214 1 098 0 175 0 18 1 155 1 575 1 635 0 355 0 295 0 805 0 135 2 145 0 955 0 575 0 735 0 435 0 855 0 8 1 705 lysozyme renal amyloidosis N639 chemokine C C motif receptor 1 AA036881 0 524 1 233 1 459 0 095 0 122 0 196 0 101 0 942 0 2 0 133 0 549 0 763 0 059 interferon gamma inducible protein 0 181 0 062 0 37 0 064 0 418 0 33 0 098 0 289 1 042 0 332 0 907 1 056 0 8 0 193 0 789 1 25 cystatin B stefin B H22919 0 188 0 489 0 603 0 074 0 212 0 295 0 54 0 535 0 453 0 479 0 021 0 291 0 651 0 536 0 401 0 511 cathepsin S AA236164 0 791 0 334 0 316 0 723 0 46 0 39 0 452 0 413 1 063 0 849 1 088 0 94 1 291 small inducible cytokine A2 monoc 0 2665 0 2955 0 5315 0 1285 0 4255 1 099 0 7265 0 6035 1 052 1 438 0 1355 0 0365 0 4335 0 0875 1 218 0 7785 0 483 0 348 0 575 0 685 0 971 0 335 0 222 0 116 1 644 0 66 0 322 0 885 0 08 0 02 0 441 0 51 natural killer cell transcript 4 AA458 superoxide dismutase 2 mitochond 0 431 0 301 0 836 0 519 0 492 0 834 0 86 0 781 0 005 1 163 1 283 0 969 0 586 0 6835 0 4865 0 6925 0 7895 0 6005 0 5815 0 4995 0 0165 0 3755 0 1225 1 129 1 137 0 6935 superoxide dismutase 2 mitochondrial AA4877 0 3185 transforming growth factor beta ind 0 0235 0 6525 0 3785 0 5505 0 3675 0 4755 0 1105 0 3435 0 0785 0 4735 0 7925 1 532 0 3355 0 0885 0 2495 0 1985 1 122 1 412 1 275 1 764 0 611 1 259 1 25 0 76 2 159 1 72 1 017 0 972 0 715 0 543 0 658 0 818 glycine dehydrogenase decarboxy syndecan 2 heparan sulfate proteo 1 828 1 7 1 409 1 964 0 975 1 516 1 24 1 75 2 219 2 477 1 08 0 29 1 641 2 045 0 315 1 356 1 726 1 892 1 568 1 528 1 346 2 157 3 114 3 146 0 943 0 236 1 349 1 674 0 416 1 557 glutathione S transferase pi R33642 chitinase 3 like 2 AA668821 0 771 1 436 1 454 0 813 1 578 0 312 0 167 0 0 469 0 129 0 566 0 489 nuclear factor I B W87528 0 464 1 314 0 187 1 429 0 189 0 551 1 94 1 372 2 152 1 825 0 441 0 928 0 316 1 188 ras homolog gene family member 1 382 0 471 0 421 0 304 0 448 0 805 0 …
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