Institute of Big data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, 1139 Shifu Avenue, Taizhou, 318000, China.
Institute of Pharmaceutical Biotechnology, School of Medicine, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310058, China.
Database (Oxford). 2020 Nov 20;2020. doi: 10.1093/database/baaa086.
Rattus norvegicus, or the rat, has been widely used as animal models for a diversity of human diseases in the last 150 years. The rat, as a disease model, has the advantage of relatively large body size and highly similar physiology to humans. In drug discovery, rat models are routinely used in drug efficacy and toxicity assessments. To facilitate molecular pharmacology studies in rats, we present the predicted rat interactome database (PRID), which is a database of high-quality predicted functional gene interactions with balanced sensitivity and specificity. PRID integrates functional gene association data from 10 public databases and infers 305 939 putative functional associations, which are expected to include 13.02% of all rat protein interactions, and 52.59% of these function associations may represent protein interactions. This set of functional interactions may not only facilitate hypothesis formulation in molecular mechanism studies, but also serve as a reference interactome for users to perform gene set linkage analysis (GSLA), which is a web-based tool to infer the potential functional impacts of a set of changed genes observed in transcriptomics analyses. In a case study, we show that GSLA based on PRID may provide more precise and informative annotations for investigators to understand the physiological mechanisms underlying a phenotype and lead investigators to testable hypotheses for further studies. Widely used functional annotation tools such as Gene Ontology (GO) analysis, and Database for Annotation, Visualization and Integrated Discovery (DAVID) did not provide similar insights. Database URL: http://rat.biomedtzc.cn.
挪威褐鼠，又称大鼠，在过去的 150 年中，被广泛用作多种人类疾病的动物模型。作为疾病模型，大鼠具有体型相对较大且与人类高度相似的生理学特点的优势。在药物发现中，大鼠模型通常用于药物功效和毒性评估。为了促进大鼠分子药理学研究，我们提出了预测大鼠互作组数据库（PRID），这是一个具有高灵敏度和特异性的高质量预测功能基因互作的数据库。PRID 整合了来自 10 个公共数据库的功能基因关联数据，推断出 305939 个假定的功能关联，预计这些功能关联将包含大鼠所有蛋白互作的 13.02%，其中 52.59%的功能关联可能代表蛋白互作。这组功能互作不仅可以促进分子机制研究中的假说制定，还可以作为参考互作组，供用户进行基因集连锁分析（GSLA）。GSLA 是一种基于转录组分析中观察到的一组变化基因来推断其潜在功能影响的网络工具。在案例研究中，我们表明，基于 PRID 的 GSLA 可以为研究人员提供更精确和有信息量的注释，以了解表型背后的生理机制，并引导研究人员提出可进一步研究的可检验假说。广泛使用的功能注释工具，如基因本体论（GO）分析和数据库注释、可视化和综合发现（DAVID），并没有提供类似的见解。数据库网址：http://rat.biomedtzc.cn。
