Multiscale Computational Oncology Research Core

多尺度计算肿瘤学研究核心(M-CORE) 多尺度计算肿瘤学研究核心(M-core)提供计算肿瘤学 从初始实验设计和电源研究到持续数据生成和数据分析的专业知识 单细胞和基因组数据的存储和共享。核心领导者费尔蒂希博士是单细胞多细胞培养领域的领导者 应用于癌症的组学，特别侧重于转化型胰腺癌的研究应用。 M-CORE将支持所有三个三态胰腺癌TBEL的高通量数据分析 (三方协定)中心项目和合作项目。方法将应用于空间和时间的桥梁 标度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的、细胞间的相互作用，这些相互作用介导了恶性肿瘤的发展 以及结合Tri-PACT新的三维成像技术的肿瘤启动。其中许多 核心领导者最近开发了方法，并将专门开发新的算法来满足 TBEL需要并提供跨项目的协同效应。研究项目将成为新单细胞的试验台 动态空间处理方法和新的成像技术，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以实现元数据 生物模型和人类先兆损伤之间的分析，项目中的生物机制， 以及通过更广泛的tbel中的跨疾病分析与癌前病变相关的新机制 与协调和数据管理中心(CDMC)合作的财团。核心领导者将 参加中心的所有定期会议，并与TBEL CDMC密切合作，以确保充足的 为新的研究方向提供计算资源。核心将与Tbel CDMC合作，以协助 数据标准和协调、数据验证、数据争论和总体数据存储、数据和 软件共享和基因组数据共享。总而言之，M-core将支持整个TBEL研究 目的通过提供计算机方法来描述恶性肿瘤发生和发展的机制。 进展为侵袭性肿瘤；分析空间和时间数据以推断相互作用和串扰 癌前细胞与间质细胞、微环境中的其他细胞；并进行整合 通过确定共享机制来促进三方协定和联盟协同作用的分析。

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.