Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Stud Health Technol Inform. 2021 Nov 18;287:109-113. doi: 10.3233/SHTI210826.
Recent studies demonstrated that comparative analysis of stem cell research data sets originating from multiple studies can produce new information and help with hypotheses generation. Effective approaches for incorporating multiple diverse heterogeneous data sets collected from stem cell projects into a harmonized project-based framework have been lacking. Here, we provide an intelligent informatics solution for integrating comprehensive characterizations of stem cells with research subject and project outcome information. Our platform is the first to seamlessly integrate information from iPSCs and cancer stem cell research into a single platform, using a multi-modular common data element framework. Heterogeneous data is validated using predefined ontologies and stored in a relational database, to ensure data quality and ease of access. Testing was performed using 103 published, publicly-available iPSC and cancer stem cell projects conducted in clinical, preclinical and in vitro evaluations. We validated the robustness of the platform, by seamlessly harmonizing diverse data elements, and demonstrated its potential for knowledge generation through the aggregation and harmonization of data. Future aims of this project include increasing the database size using crowdsourcing and natural language processing functionalities. The platform is publicly available at https://remedy.mssm.edu/.
最近的研究表明，对来自多个研究的干细胞研究数据集进行比较分析可以产生新的信息，并有助于假设的产生。将来自干细胞项目的多个不同异质数据集纳入协调的基于项目的框架中的有效方法一直缺乏。在这里，我们提供了一种智能信息学解决方案，用于将干细胞的综合特征与研究对象和项目结果信息集成在一起。我们的平台是第一个将 iPSCs 和癌症干细胞研究的信息无缝集成到单个平台中的平台，使用多模块通用数据元素框架。使用预定义的本体对异构数据进行验证，并将其存储在关系数据库中，以确保数据质量和易于访问。使用在临床、临床前和体外评估中进行的 103 个已发表的公开可用的 iPSC 和癌症干细胞项目对其进行了测试。我们通过无缝协调不同的数据元素验证了平台的稳健性，并通过数据的聚合和协调展示了其生成知识的潜力。该项目的未来目标包括使用众包和自然语言处理功能增加数据库大小。该平台可在 https://remedy.mssm.edu/ 上公开获取。
