Core 3: Integrative Models of Aging Core

项目概要-老化核心的综合模型 老龄化是一个多方面、多尺度和异质性的过程。虽然特定的途径和基因 与衰老相关的研究开始从计算模型研究中出现，在高- 通量和单细胞测序，蛋白质组学和成像分析，衰老领域的研究人员必须 克服了许多挑战，以整合和解释这些不同的，往往是巨大的数据集。 由于这种高门槛的进入，衰老生物学的研究人员才刚刚开始研究 使用综合数据驱动方法进行老化。为了支持圣地亚哥内森休克中心的使命 卓越的基础生物学老化（SD-NSC），衰老核心的综合模型（建模核心） 将通过设计高通量数据的生成和管理策略来应对这些挑战， 开发新的综合算法和模型，用于询问衰老生物学的特定方面， 包括细胞异质性的作用，并通过可访问的在线门户网站实现这些模型。的 Modeling Core提出了以下三个具体目标。首先，核心将建立足够的数据 基础设施演进综合建模需要从不同的高质量预处理数据中获得高质量的数据， 测定通量。该目标将确定并实施预先部署所需的硬件和软件资源， 处理和存储测序、蛋白质组学、代谢组学和成像数据。第二，核心将实施 并开发出考虑到老化过程异质性的综合模型。综合 计算模型将使不同的预处理数据输入映射到集成的 可解释的生物过程。然后，这些模型可用于生成可被检验的假设 在实验室中，导致生成额外的数据集，这些数据集可用于在 迭代的方式。这方面的工作将包括：（1）满足应用现有技术的要求， 数据的综合分析，以及2）开发定制的预测计算模型作为工具， 回答关于衰老生物学的具体问题。最后，核心将提供广泛的访问， 集成建模工具。虽然计算模型允许系统地了解特定的老化- 相关的生物过程，将需要广泛获得这些模型，以最大限度地影响整个 神经干细胞和整个老化领域。这一目标的重点是将模型和理论转化为互动的 供衰老生物学研究人员使用的工具。

PROJECT SUMMARY – Integrative Models of Aging Core Aging is a multi-faceted, multi-scale and heterogeneous process. While specific pathways and genes associated with aging are beginning to emerge from computational modeling studies, in the age of high- throughput and single-cell sequencing, proteomic, and imaging analyses, researchers in the aging field must overcome a number of challenges to integrate and interpret these disparate and often massive datasets. Because of this high barrier to entry, biology of aging researchers are only beginning to approach the study of aging using integrated data-driven approaches. To support the mission of the San Diego Nathan Shock Center of Excellence in the Basic Biology of Aging (SD-NSC), the Integrative Models of Aging Core (Modeling Core) will address these challenges by devising strategies for the generation and curation of high-throughput data, developing novel integrative algorithms and models for interrogating specific aspects of aging biology, including the role of cellular heterogeneity, and implementing these models via an accessible online portal. The Modeling Core proposes the following three specific aims. First, the Core will establish sufficient data infrastructure. Integrative modeling requires high quality pre-processed data obtained from diverse high- throughput assays. This Aim will identify and implement the hardware and software resources required to pre- process and store sequencing, proteomics, metabolomics, and imaging data. Second, the Core will implement and develop integrative models of aging that take into account the heterogenicity of the process. Integrative computational models will enable the mapping of diverse pre-processed data inputs into integrated interpretable biological processes. These models can then be used to generate hypotheses that can be tested in the lab, resulting in the generation of additional datasets, which can be used to refine the models in an iterative manner. Work in this aim will consist of: 1) fulfilling requests to apply established techniques for the integrative analysis of data, and 2) developing customized predictive computational models as tools for answering specific questions regarding aging biology. Finally, the Core will provide widespread access to integrative modeling tools. While computational models allow for a systematic understanding of specific aging- related biological processes, widespread access to these models will be needed to maximize impact across NSCs and across the field of aging. This aim is focused on translating the models and theories into interactive tools for use by aging biology researchers.