title: Dose-response modeling in reproductive toxicology in the systems biology era.
abstract: Systems biology approaches for modeling cellular signaling networks affected by chemical exposures should soon produce integrated methodologies capable of predicting dose-response relationships for developmental toxicants and for other toxic responses. This paper outlines an emerging strategy for systems biology approaches in dose-response modeling. Genome-wide functional screens, bioinformatic tools, and network mapping technologies together can provide directed graph representations of the cellular signaling networks. The graphical representations can be converted into mathematical models that permit predicting the shapes of dose-response curves for altered cell signaling by test compounds during development. Systems biology approaches require interdisciplinary teams with expertise in reproduction, cell biology, signal transduction, mathematical/biomedical modeling, and risk assessment. In addition to outlining a systems approach for dose-response research, this paper discusses initial stages of application of this strategy to examine inhibition of steroidogenesis in testes by phthalate esters.
authors.affiliation: CIIT Centers for Health Research, Research Triangle Park, NC 27709-2137, USA. MAndersen@ciit.og
authors.forename: Melvin E
authors.initials: ME
authors.lastname: Andersen
authors.forename: Russell S
authors.initials: RS
authors.lastname: Thomas
authors.forename: Kevin W
authors.initials: KW
authors.lastname: Gaido
authors.forename: Rory B
authors.initials: RB
authors.lastname: Conolly
mesh_terms: D000818:Animals; D002477:Cells / Q000378:metabolism; D019295:Computational Biology; D004305:Dose-Response Relationship, Drug; D023281:Genomics; D006801:Humans; D008954:Models, Biological; D012098:Reproduction; D018570:Risk Assessment; D015398:Signal Transduction; D049490:Systems Biology; D014116:Toxicology / Q000379:methods* / Q000639:trends; D015262:Xenobiotics / Q000633:toxicity
chemical_list: D015262:Xenobiotics