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TISSUES 2.0: an integrative web resource on mammalian tissue expression

机译:组织2.0:有关哺乳动物组织表达的综合网络资源

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摘要

Physiological and molecular similarities between organisms make it possible to translate findings from simpler experimental systems—model organisms—into more complex ones, such as human. This translation facilitates the understanding of biological processes under normal or disease conditions. Researchers aiming to identify the similarities and differences between organisms at the molecular level need resources collecting multi-organism tissue expression data. We have developed a database of gene–tissue associations in human, mouse, rat and pig by integrating multiple sources of evidence: transcriptomics covering all four species and proteomics (human only), manually curated and mined from the scientific literature. Through a scoring scheme, these associations are made comparable across all sources of evidence and across organisms. Furthermore, the scoring produces a confidence score assigned to each of the associations. The TISSUES database (version 2.0) is publicly accessible through a user-friendly web interface and as part of the STRING app for Cytoscape. In addition, we analyzed the agreement between datasets, across and within organisms, and identified that the agreement is mainly affected by the quality of the datasets rather than by the technologies used or organisms compared. >Database URL:
机译:生物之间的生理和分子相似性使得将来自简单的实验系统(模型生物)的发现转化为更复杂的发现(例如人类)成为可能。这种翻译有助于理解正常或疾病条件下的生物过程。旨在在分子水平上识别生物之间的异同的研究人员需要收集多种生物组织表达数据的资源。通过整合多种证据来源,我们已经建立了人类,小鼠,大鼠和猪中基因-组织关联的数据库:涵盖所有四种物种的转录组学和蛋白质组学(仅人类),是从科学文献中人工挑选和提取的。通过评分方案,可以使这些关联在所有证据来源和生物体之间具有可比性。此外,计分产生分配给每个关联的置信度得分。 TISSUES数据库(2.0版)可通过用户友好的Web界面公开访问,并且作为Cytoscape的STRING应用的一部分。此外,我们分析了生物体之间和生物体内的数据集之间的协议,并确定该协议主要受数据集质量的影响,而不是受所用技术或比较生物的影响。 >数据库网址

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