STOCHASTIC MODELS OF CARCINOGENESIS--ANALYSES OF EPIDEMIOLOGIC/EXPERIMENTAL DATA

项目1的重点是发展的随机模型， 使用这些模型的致癌作用和实验数据。 具体 该项目的目标分为三组。 1. 肿瘤数据时间的风险函数和分析。 在本部中 我们将研究风险函数的性质， 两突变克隆扩张模型及其扩展 特别是，我们建议调查的问题，可识别性，善良- 拟合度、肿瘤检测时间的纳入、暴露于 环境因子、危险函数的近似值和协变量 测量误差。 2. 中间（癌前）病变的数量和大小分布 以及启动-促进实验的分析。 在这部分 项目，我们将开发模型，用于分析 啮齿动物肝脏或小鼠皮肤上的乳头状瘤。 特别是要 研究用于体视学重建的无形状方法， 啮齿类动物肝脏病灶的分析及其分析方法 小鼠皮肤上乳头状瘤的相关纵向数据。 3. 开发高效的计算算法。 我们打算 开发高效的计算机算法和软件，包括高度 计算机密集型方法，如马尔可夫链蒙特卡罗方法， 使用1和2中开发的模型分析数据。

The focus of Project 1 is the development of stochastic models of carcinogenesis and experimental data using these models. The specific aims of this project fall into three groups. 1. The hazard function and analyses of time to tumor data. In this part of the project, we will investigate the properties of the hazard function of the two-mutation clonal expansion model and extensions of it. In particular, we propose to investigate issues of identifiability, goodness- of-fit, incorporation of time to tumor-detection, patterns of exposure to environmental agents, approximations to the hazard function, and covariate measurement errors. 2. Number and size distribution of intermediate (premalignant) lesions and analyses of initiation-promotion experiments. In this part of the project, we will develop models for the analyses of altered foci in the rodent liver or papillomas on the mouse skin. In particular, we will investigate shape-free methods for stereological reconstruction and analyses of foci in the rodent liver and methods for analyses of correlated longitudinal data on papillomas on the mouse skin. 3. Development of efficient computational algorithms. We intend to develop efficient computer algorithms and software, including highly computer-intensive methods such as Markov Chain Monte Carlo methods, for analyzing data using the models developed in 1 and 2.