Biomedical Informatics Core

临床和转化性癌症研究的目标是迅速将新的进展转化为BASE 研究以改善病人护理，并传达来自临床研究的结果，这些新的和 越来越多的定制化诊断和治疗回到工作台上，以进一步完善我们的 对肿瘤发生的理解。为了实现这一目标，内科科学家必须能够整合不同的 以及包括从患者或具有结果的参与者那里获得的临床信息的复杂数据集 常规实验室测试、成像、生物样品、分子图谱(例如微阵列分析、蛋白质组学、 和脂质组学)，以及基因组注释信息。必须对这些数据进行协同分析和可视化，才能获得 对疾病过程有全面的了解。此外，获得阿里的这一信息和 分析结果必须无缝地提供给内科医生、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？计算机科学的应用和 信息技术对医疗保健和生物医学研究中的数据管理问题的解决 有效翻译研究的关键和必要组成部分。要在SCC内满足这一需求 生物信息学核心(现更名为生物医学信息学核心)创建于2002年。 正如名称更改所反映的那样，随着时间的推移，核心的服务不仅满足了 与管理、存储和分析高维数据相关的信息学/计算挑战 数据集(例如微阵列、蛋白质组和NextGen测序数据集)，而且还支持语法和 表示、存储和共享临床研究/试验和生物样品数据集所需的语义需求。 这些后一种活动和服务是由我们对caBlG？的参与和领导所推动的 吴氏生物医学信息学中心的首创和联合 整合了许多不同的基于P30的核心和CTSA的人员、硬件和软件 生物医学信息学项目。

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.