Protein regulatory relationships in COVID19

This dataset was extracted from the Elsevier Pathway Studio, a tool that helps scientists analyze experimental data to answer biologically meaningful questions. The dataset itself consists of biological relationships between diseases (MERS and SARS), proteins and molecules. The relationships are of various types including Regulation, Target, Molecular Transport, etc. You can find a mapping of the relationship name to a description on this support page: https://service.elsevier.com/app/answers/detail/a_id/3014/supporthub/pathway/

The source of these relationships are life sciences and biomedical articles, from various publishers. We make use of taxonomies, curated and maintained by subject matter experts, to extract the right terms from text and map them to the correct identifiers. Subject matter experts have also helped us create the rules and information extraction patterns to optimize the extraction of relationships from text.

At last, the pubmed identifiers from which the relationships were extracted are also part of the dataset.
The .cypher and .json files can be imported into the graph database neo4j. The .csv files can be used to import into other systems.

本数据集源自Elsevier Pathway Studio，该工具辅助科学家分析实验数据，以解答生物学上的相关问题。数据集本身包含了疾病（如中东呼吸综合征MERS和严重急性呼吸综合征SARS）、蛋白质与分子之间的生物学关系。这些关系类型多样，包括调控、靶点、分子运输等。您可以在以下支持页面找到关系名称与描述的映射：https://service.elsevier.com/app/answers/detail/a_id/3014/supporthub/pathway/。这些关系的来源是生命科学和生物医学领域的文章，来自不同的出版商。我们利用由领域专家编纂和维护的术语分类，从文本中提取正确的术语并将它们映射到相应的标识符。领域专家还协助我们制定规则和信息提取模式，以优化从文本中提取关系。最后，数据集中还包含了提取这些关系的PubMed标识符。.cypher和.文件可以导入到图数据库neo4j中，而.csv文件则可用于导入其他系统。