Glucocorticoid receptor regulatory network (v2.0)

This is the updated version of an original NCI Pathway Interaction Database (PID) network.
The list of entities (genes, proteins, chemicals, etc) from the original network was used to query the INDRA database, retrieving high-quality relationships between entities. INDRA is a database that integrates information from multiple high-quality text mining engines, pathway databases, and small molecule resources. The INDRA-derived relationships are up-to-date and have links to detailed summaries of supporting literature evidence, including the specific supporting text.
While we have included only high-confidence relationships, text-mining complicated sentences can produce errors such as the reversal of up-regulation vs. down-regulation or the direction of an edge (i.e. B activates A instead of A activates B). Nevertheless, the entity recognition by the text miners is excellent and the text supporting a relationship almost always describes a genuine relationship between the entities.
Legend:
BLUE: edges annotated by INDRA only.
RED: edges annotated both by INDRA and PID.
YELLOW: selected element.

本数据集为原始NCI通路相互作用数据库（NCI Pathway Interaction Database，PID）网络的更新版本。
我们采用原始网络中的实体（基因、蛋白质、小分子化合物等）列表检索INDRA数据库，获取实体间的高质量关联关系。INDRA是一款整合了多种高质量文本挖掘引擎、通路数据库以及小分子资源信息的数据库。由INDRA衍生得到的关联关系具备时效性，且附带支持性文献证据的详细摘要，包含具体的支撑文本片段。
尽管我们仅纳入了高置信度的关联关系，但文本挖掘处理复杂语句时可能产生误差，例如上调与下调关系的反转，或是边的方向标注错误（如将B激活A误标注为A激活B）。尽管如此，文本挖掘工具对实体的识别效果优异，且支撑关联关系的文本几乎总能准确描述实体间的真实关联。
图例说明：
蓝色：仅由INDRA标注的边。
红色：同时由INDRA与PID标注的边。
黄色：选中的元素。