Dose-response Methods Development for High Throughput, Nontraditional, and Standard Bioassays

高通量、非传统和标准生物测定的剂量响应方法开发

• 批准号: 10928618
• 负责人: Matthew Wheeler
• 金额: $ 11.28万
• 依托单位: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10928618
• 关键词: Bayesian Analysis; Benchmarking; Biological Assay; Biological Process; Chemicals; Complex; Data; Dose; Estimation Techniques; Genes; Goals; Literature; Methodology; Mission; Modeling; National Toxicology Program; Research; Techniques; Toxic effect; Toxicogenomics; Toxicology; data streams; gene network; method development; novel; response; tool

This research develops novel dose-response methodologies for estimating toxicity using Bayesian analyses. To estimate the point of departure for toxicity, the research extends the use of benchmark dose estimation techniques to new dose-response methodologies. Though some of the parametric tools available in the literature, they are often inadequate for the needs of toxicogenomic and high-throughput data streams. Consequently, non-parametric models that simultaneously estimate the correlation between multiple bioassays and genes will be developed, and network analytic techniques will be developed to find gene-networks.

这项研究开发了新的剂量反应方法，估计使用贝叶斯分析的毒性。 为了估计毒性的出发点，该研究将基准剂量估计技术的使用扩展到新的剂量反应方法。 虽然一些参数化的工具，在文献中，他们往往是不够的毒理基因组学和高通量数据流的需要。 因此，将开发同时估计多个生物测定和基因之间的相关性的非参数模型，并开发网络分析技术以找到基因网络。