Cross Training Core

交叉训练核心

• 批准号: 10515455
• 负责人: Luigi Marchionni
• 金额: $ 20.93万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-04 至 2027-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10515455
• 关键词: Address; Algorithmic Software; Basic Science; Big Data; Bioinformatics; Biology; Biometry; Clinical Sciences; Collaborations; Communities; Complex; Computational Biology; Computing Methodologies; Data; Data Science; Data Storage and Retrieval; Development; Elements; Ensure; Evolution; Faculty; Fostering; Generations; Genomics; Image; Image Analysis; Institution; Investigation; Laboratories; Laboratory Scientists; Learning; Light; Liquid substance; Malignant Neoplasms; Malignant neoplasm of prostate; Medicine; Methodology; Methods; Mission; Modernization; Molecular Analysis; Pathology; Persons; Population; Positioning Attribute; Process; Production; Radiation Oncology; Recording of previous events; Reproducibility; Research; Research Design; Research Personnel; Research Project Grants; Resources; Role; Scientist; Standardization; Systems Biology; Technology; Training; Training Activity; Work; algorithmic methodologies; analytical method; cloud based; data integration; data sharing; educational atmosphere; experience; file format; genome sciences; genomic data; hands-on learning; in situ imaging; innovation; interest; medical schools; meetings; member; metabolomics; multimodal data; multimodality; novel; programs; radiomics; tool; transcriptomics

The Cross-Training Core (CTC) for the U54 ROBIN OligoMET Center will consist of experienced faculty members of the Division of Computational and Systems Biology (CSP) in the Department of Pathology and Laboratory Medicine of Weill Cornell Medical College (WCM). The team at WCM will work in close collaboration with teams at the other Institutions, and a history of collaboration already exists between the CTC team members and the investigators leading the Research Projects and the other Research Cores, which will further ensure the successful progression of the Center. The CTC activities will be centered around the following purposes: Aim 1) To provide a unified analytical framework across the U54 ROBIN OligoMET Center to foster cross-project data integration and comparison. Imaging, omics, and radiomics data are found in a variety of forms (e.g., different platforms, file formats, etc.), and training people on how to manage each of these instances is challenging and inefficient. We will have unified analytical framework within the U54 ROBIN OligoMET Center where data is aggregated and standardized, greatly decreases the training complexity and increases reproducibility which results in a more fluid training process. Aim 2) To provide educational support and training across the U54 ROBIN OligoMET Center. Advances in genomics, transcriptomics, metabolomics, and radiomics technologies have led to exponential rises in both production and availability of multimodal data. In light of these rapid evolutions, disseminating the latest bioinformatics methods within the U54 Center – and the broader biomedical community – is a challenge of paramount importance. The CTC will address such challenge by creating an open educational platform that will provide a rich interactive learning environment, leveraging a cloud-based framework to collaboratively create and share tutorials and learning experiences. To this end, the CTC will build upon a 10- year experience in the computational genomics and data science domains and training biologists and clinicians in computational methods. Aim 3) To develop novel analytical approaches for the comprehensive characterization of oligometastatic prostate cancer (PCa) via integrated analyses of multimodal big data. Omics and radiomics technologies, multiparametric in situ imaging, and spatially-resolved molecular and image analyses are rapidly evolving fields. Therefore, continually evolving technologies, software, algorithms, and analytical methods are efforts of essence. PCa investigations across the U54 ROBIN OligoMET Center encompass a multitude of these domains, hence it is of paramount importance that a versatile and innovative portfolio of approaches is developed to fully support the ongoing and future research. The U54 ROBIN OligoMET Center will therefore provide an ideal platform for such cross-disciplinary training, and the CTC will support such crucial endeavor through developing and disseminating ad-hoc training modules across the whole U54 ROBIN OligoMET Center and the other ROBIN Centers.

U54 Robin Poligomet中心的交叉训练核心（CTC）将由经验丰富的教师组成 病理学系计算与系统生物学（CSP）的成员 威尔·康奈尔医学院（WCM）的实验室医学。 WCM的团队将密切合作 在其他机构的团队中，CTC团队成员之间已经存在合作历史 研究人员领导研究项目和其他研究核心，这将进一步确保 中心的成功发展。 CTC活动将以以下目的为中心：目标1） 为了在U54 robin寡仪中心提供统一的分析框架以培养跨项目数据 集成和比较。成像，奥理和放射线学数据以多种形式（例如，不同的形式）发现 平台，文件格式等），并培训人们如何管理这些实例都是挑战和 效率低下。我们将在U54 Robin寡中中心内拥有统一的分析框架 汇总和标准化，大大降低了训练的复杂性并增加了可重复性 导致更流畅的训练过程。目标2）在U54 Robin上提供教育支持和培训 寡中中心。基因组学，转录组学，代谢组学和放射组技术的进步已领导 在多模式数据的生产和可用性方面呈指数增长。鉴于这些快速发展， 传播U54中心内的最新生物信息学方法 - 以及更广泛的生物医学界 - 是至关重要的挑战。 CTC将通过建立开放教育来应对此类挑战 将提供丰富的互动学习环境的平台，利用基于云的框架 协作创建和分享教程和学习经验。为此，CTC将基于10- 计算基因组学和数据科学领域以及培训生物学家和临床医生的年度经验 在计算方法中。目标3）开发新的分析方法 通过多模式大数据的综合分析来表征寡聚前列腺癌（PCA）。 omics 和放射学技术，多参数原位成像，以及空间分辨的分子和图像 分析是迅速发展的领域。因此，不断发展的技术，软件，算法和 分析方法是本质的努力。 U54罗宾寡中中心的PCA调查 涵盖了许多这些领域，因此，具有多功能和创新性的重要性至关重要 开发了方法组合是为了充分支持正在进行的和未来的研究。 U54罗宾寡量 因此，中心将为这种跨学科培训提供理想的平台，CTC将支持此类 通过开发和传播整个U54 Robin的临时培训模块的关键努力 寡中中心和其他知更鸟中心。