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.

本数据集提取自爱思唯尔（Elsevier）Pathway Studio工具——一款可助力科研人员分析实验数据、解答具有生物学意义研究问题的专业工具。数据集本身涵盖疾病（中东呼吸综合征（MERS）、严重急性呼吸综合征（SARS））、蛋白质与分子之间的各类生物学关联，关联类型包括调控（Regulation）、靶点（Target）、分子转运（Molecular Transport）等。用户可通过该支持页面查询关联名称与对应描述的映射关系：https://service.elsevier.com/app/answers/detail/a_id/3014/supporthub/pathway/。上述关联的来源为多家出版商出版的生命科学与生物医学学术文献。本数据集依托由领域专家整理维护的分类体系，从文本中提取精准术语并映射至正确标识符。此外，领域专家还协助制定了规则与信息抽取模式，以优化从文本中提取关联的效果。最后，提取得到关联所对应的PubMed标识符也被纳入本数据集。其中，.cypher与.json格式文件可导入图数据库Neo4j，.csv格式文件则可用于导入其他系统。