Multiscale Computational Oncology Research Core

多尺度预防性肿瘤学研究核心（M-CORE）-摘要 多尺度计算肿瘤学研究核心（M-CORE）提供计算肿瘤学 从最初的实验设计和功率研究到持续的数据生成和数据分析， 单细胞和基因组学数据的存储和共享。核心领导人Fertig博士是单细胞多细胞生物技术领域的领导者， 组学应用于癌症，特别关注转化胰腺癌研究应用。 M-CORE将支持所有三种三态胰腺癌TBEL的高通量数据分析 （Tri-PACT）中心项目和合作项目。方法将被应用于桥梁空间和时间 量表，以确定癌前病变进展为浸润性癌症的细胞内在机制。 这些将被扩展到分析细胞外在的，介导恶性肿瘤发展的细胞间相互作用 以及结合Tri-PACT新三维成像技术的肿瘤启动。许多这些 核心领导人最近开发了一些方法，新的算法将专门开发，以满足 TBEL需要并提供跨项目的协同作用。研究项目将成为新单细胞的试验台 动态空间过程和新型成像技术的方法，以及计算协作 项目将受益于M-CORE资源。核心中的标准化将协调数据， 生物模型和人类前驱病变之间的分析，项目的生物机制， 通过更广泛的TBEL中的交叉疾病分析， 协调和数据管理中心（CDMC）。核心领导人将 参加中心的所有定期会议，并与TBEL CDMC密切合作，以确保 新的研究方向的计算资源。核心将与TBEL CDMC合作， 数据标准和协调，数据验证，数据争论，以及整体数据存储，数据和 软件共享和基因组数据共享。总之，M-CORE将支持整个TBEL研究 目的通过提供计算方法来表征恶性肿瘤发生的机制， 发展为侵袭性肿瘤;分析空间和时间数据，以推断 癌前细胞与基质细胞和微环境中的其他细胞;并进行整合 通过确定共同机制，促进《三方协定》和联合会的协同作用。

MULTISCALE COMPUTATIONAL ONCOLOGY RESEARCH CORE (M-CORE) – Abstract The Multiscale Computational Oncology Research Core (M-CORE) provides computational oncology expertise from initial experimental design and power studies to ongoing data generation and analysis to data deposition and sharing for single-cell and genomics data. Core Leader Dr. Fertig is a leader in single-cell multi- omics for applications to cancer, with a particular focus on translational pancreatic cancer research applications. The M-CORE will support high-throughput data analysis in all three Tri-State Pancreatic Adenocarcinoma TBEL (Tri-PACT) Center Projects and Collaborative Projects. Methods will be applied to bridge spatial and temporal scales to identify cell intrinsic mechanisms underlying pre-malignant lesions progression into invasive cancers. These will be extended to analyze cell extrinsic, intercellular interactions that mediate malignancy development and tumor initiation incorporating new three-dimensional imaging technologies from Tri-PACT. Many of these methods were recently developed by the Core leader, and new algorithms will be developed specifically to meet the TBEL needs and provide synergy across Projects. Research Projects will be testbeds for new single-cell methods for dynamic spatial processes and novel imaging technologies, and computational Collaborative Projects will benefit from M-CORE resources. Standardization in the Core will harmonize data to enable meta- analyses between biological models and human precursor lesions, biological mechanisms from the Projects, and novel mechanisms associated with precancer through cross-disease analysis in the broader TBEL consortium in collaboration with the Coordinating and Data Management Center (CDMC). The Core Leader will participate in all regular Center meetings and collaborate closely with the TBEL CDMC to ensure ample computational resources for new research directions. The Core will partner with the TBEL CDMC to assist with data standards and harmonization, data validation, data wrangling, and overall data deposition, data and software sharing, and genomic data sharing. In summary, the M-CORE will support the overall TBEL research objectives by providing computational methods to characterize the mechanisms of malignancy initiation and progression into invasive tumors; to analyze spatial and temporal data to infer interactions and crosstalk between pre-malignant cells with stromal cells, and other cells in the microenvironment; and to perform integrative analyses to promote Tri-PACT and Consortium synergy by identifying shared mechanisms.