UAB Pilot Center for Precision Animal Modeling (C-PAM) - Bioinformatics Section

摘要（生物信息学部分） UAB精确动物建模中心（C-PAM）的目标是有效分析和建模， 作为罕见病项目的一部分，确定变异，以提供明确的诊断，评估特定变异 影响，并支持治疗靶点识别。C-PAM将通过应用 计算、细胞和临床方法，以帮助产生信息丰富的动物模型。作为 该中心的组成部分，C-PAM生物信息学部分（BIS）将提供计算工具，方法， 和分析，支持必要的和多样化的可视化、探索和分析用例集。它 支持具有不同技能和兴趣的内部和外部C-PAM用户，并支持相关用例 人类和动物模型数据以及它们之间的交叉点。通过裁剪现有的软件 基础设施、计算方法和分析能力，BIS将提供C-PAM 计算框架（门户、储存库和分析）。 BIS将：支持关于选择模型变体的决策（I、II期），预测表型 结果（III期），收集和传播动物模型生成过程中的数据（IV、V期）， 与C-PAM部门和生物医学界分享数据和方法（第六、五阶段）， 支持C-PAM影响评估。面向外部的C-PAM门户（目标1）将提供数据访问 和分析以及整个中心的统一视图，包括中心的持有和访问的会计 数据和工具。我们的数据模式完全是数据驱动的，高度数据压缩，允许定制 以及随底层数据源更新而按需更新。此外，它还旨在支持 C-PAM的自然工作流程，例如通过为用户提供添加注释的能力 和策展，确保知识不会丢失到外部记事本或应用程序中。同时，在现有的 功能（目标2），门户将集成一组多样化的分布式工具和数据存储， 考虑、优先排序和选择用于模式生物研究的变体。这套 这些功能将支持用户预测和理解基因的表型结果的能力。 C-PAM产生的扰动。最后，国际清算银行将支持和容纳尖端的计算研究 用于选择和优先考虑新的或重新利用的药物靶点，以进行治疗决策（目标3）。 这些创新的机器学习和其他计算方法的应用将 支持全面的变异损伤和药物预测临床前假设检验和优先级排序。 在所有这些目标中，BIS将支持不同利益相关者的需求，包括临床医生， 患者群体，以及细胞、分子和计算生物学家。通过上述方法，BIS 将支持C-PAM的目标，即提供有效和具有成本效益的模型，可用于帮助患者或 他们的临床医生确定变异的致病性或帮助鉴定可能的治疗方法。

ABSTRACT (BIOINFORMATICS SECTION) The goal of the UAB Center for Precision Animal Modeling (C-PAM) is efficient analysis and modeling of variants identified as part of rare disease programs to provide a definitive diagnosis, evaluate specific variant impact, and support therapeutic target identification. C-PAM will accomplish this through application of computational, cellular, and clinical methods to assist in the generation of informative animal models. As a component of this Center, the C-PAM Bioinformatics Section (BIS) will provide the computational tools, methods, and analyses supporting the necessary and diverse set of visualization, exploration, and analysis use cases. It supports internal and external C-PAM users with varying skillsets and interests and supports use cases related to both human and animal model data and the intersection between them. By tailoring existing software infrastructure, computational approaches, and analytical capabilities, the BIS will provide the C-PAM computational framework (portal, repository and analyses). The BIS will: support decisions regarding selection of variants to model (Phases I, II), predict phenotypic outcomes (Phase III), collect and disseminate data from the animal model generation process (Phases IV, V), share data and methods with C-PAM sections and the biomedical community (Phases VI, V), and overall support impact evaluation for C-PAM. The outward facing C-PAM portal (Aim 1) will provide data access and analytics and a unifying view of the entire Center including an accounting of the Center's holdings and access to data and tools. Our data schema is completely data driven and highly data condensing, allowing customization and on-demand updates as underlying data sources update. Additionally, it is designed to support the natural workflow of C-PAM, for example by providing users with the ability to add notes and curations, ensuring knowledge is not lost to external notepads or apps. Also building out existing capabilities (Aim 2), the portal will integrate a diverse and distributed set of tools and data stores supporting consideration, prioritization, and selection of variants for model organism study. This suite of features will support the user's ability to predict and understand phenotypic outcomes of the genetic perturbations generated by C-PAM. Finally, the BIS will support and house cutting-edge computational research for selection and prioritization of novel or repurposed drug targets for therapeutic decision-making (Aim 3). Application of these innovative machine learning and other computational methodologies will support comprehensive variant damage and drug prediction preclinical hypothesis testing and prioritization. Across all of these aims the BIS will support the needs of diverse stakeholders, including clinicians, patient groups, and cellular, molecular, and computational biologists. Through the approaches outlined, the BIS will support the C-PAM goals of providing efficient and cost-effective models that can be used to help patients or their clinicians determine the pathogenicity of a variant or aid in identification of possible treatments.