Biomedical Informatics Core

临床和转化癌症研究的目标是快速将新进展转化为实验室 研究改善患者护理并传播采用此类新方法和新技术的临床研究结果 越来越多的定制诊断和治疗回到工作台上，以进一步完善我们的 了解肿瘤发生。为了实现这一目标，医师科学家必须能够整合不同的知识 以及复杂的数据集，包括从患者或参与者获得的临床信息及其结果 常规实验室测试、成像、生物样本、分子分析（例如微阵列分析、蛋白质组学、 和脂质组学）和基因组注释信息。这些数据必须进行共同分析和可视化才能获得 全面了解疾病过程。此外，访问所有这些信息和 分析结果必须能够无缝地提供给医生、临床科学家和实验室科学家 在组织内部和组织之间减少基础科学和临床研究之间的障碍。 鉴于这些要求，生物医学信息学领域——计算机科学和技术的应用 信息技术解决医疗保健和生物医学研究中的数据管理问题 ¿ 有效转化研究的关键和必要组成部分。 To address this need within the SCC 和WU，生物信息学核心（现更名为生物医学信息学核心）于2002年创建。 正如名称变更所反映的那样，随着时间的推移，核心的服务已经发展到不仅解决 与管理、存储和分析高维相关的布信息学/计算挑战 数据集（例如微阵列、蛋白质组和 NextGen 测序数据集），还支持句法和 表示、存储和共享临床研究/试验和生物样本数据集所需的语义需求。 后面这些活动和服务得到了我们对caBlG的参与和领导的推动。 倡议以及将 WU 的信息学合并为生物医学信息学中心 许多不同的基于 P30 的核心和 CTSA 的人员、硬件和软件的整合 Biomedical Informatics Program.

The goal of clinical and translational cancer research is to rapidly convert novel advances In bench research to improvements in patient care and to relay findings from clinical studies employing such new and increasingly customized diagnostics and therapeutics back to the bench for further refinement of our understanding of tumorigenesis. To realize this aim, the physician-scientist must be able to Integrate diverse and complex datasets that include clinical information obtained from the patient or participant with the results of routine laboratory tests, imaging, biospecimens, molecular profiling (e.g. microarray analysis, proteomics, and lipidomics), and genome annotation information. These data must be co-analyzed and visualized to gain a comprehensive understanding of the disease process. Furthermore, access to ali of this information and findings from analyses must be seamlessly available to physicians, clinician-scientists, and bench scientists both within and across organizations to reduce the barrier between basic science and clinical research. Given these requirements, the field of biomedical informatics ¿ the application of computer science and information technology to the problems of data management In healthcare and biomedical research ¿ is a critical and necessary component of effective translational research. To address this need within the SCC and WU, the Bioinformatics Core (now renamed to the Biomedical Informatics Core) was created in 2002. As reflected in the name change, over time, the Core's services have grown to address not only bloinformatics/computational challenges associated with managing, storing, and analyzing high dimensional data sets (e.g. microarray, proteomic, and NextGen sequencing data sets) but also to support syntactic and semantic needs required to represent, store, and share clinical studies/trials and biospecimen data sets. These latter activities and services have been catalyzed by our participation and leadership in the caBlG¿ Initiative as well as the coalescence of informatics at WU into the Center for Biomedical Informatics through the consolidation of personnel, hardware, and software of many different P30-based cores and the CTSA Biomedical Informatics Program.