In the past few decades, the life sciences have experienced an unprecedented accumulation of data, ranging from genomic sequences and proteomic profiles to heavy-content imaging, clinical assays, and commercial biological products for research. Traditional static databases have been invaluable in providing standardized and structured information. However, they fall short when it comes to facilitating exploratory data interrogation, real-time query, multidimensional comparison and dynamic visualization. Interactive databases aiming at supporting user-driven data queries and visualization offer promising new avenues for making the best use of the vast and heterogeneous data streams collected in biological research. This article discusses the potential of interactive databases, highlighting the importance of implementing this model in the life sciences, while going through the state-of-the-art in database design, technical choices behind modern data management systems, and emerging needs in multidisciplinary research. Special attention is given to data interrogation strategies, user interface design, and comparative analysis capabilities, along with challenges such as data standardization and scalability in data-heavy applications. Conceptual features for developing interactive databases along diverse life science domains are then presented in the user case of cell line selection for in vitro research to bridge the gap between research data generation, actionable biological insight, subsequent meaningful experimental design, and clinical relevance.

翻译：过去几十年间，生命科学领域经历了前所未有的数据积累，涵盖基因组序列、蛋白质组谱图、高内涵成像、临床检测以及商业研究用生物制品等多个维度。传统静态数据库在提供标准化、结构化信息方面具有不可估量的价值，但在支持探索性数据查询、实时检索、多维比较和动态可视化方面存在明显不足。旨在支持用户驱动型数据查询与可视化的交互式数据库，为充分利用生物研究中收集的海量异构数据流开辟了前景广阔的新途径。本文探讨交互式数据库的发展潜力，强调在生命科学领域实施该模式的重要性，同时梳理数据库设计的前沿进展、现代数据管理系统背后的技术选择以及跨学科研究中的新兴需求。研究重点关注数据查询策略、用户界面设计和比较分析功能，并探讨数据标准化及数据密集型应用可扩展性等挑战。最后以体外研究细胞系筛选的用户案例，提出适用于多领域生命科学的交互式数据库概念框架，旨在弥合研究数据生成、可操作的生物学洞见、后续有意义的实验设计与临床相关性之间的鸿沟。