TBGA: A Large-Scale Gene-Disease Association Dataset for Biomedical Relation Extraction

This repository contains the TBGA dataset. TBGA is a large-scale, semi-automatically annotated dataset for Gene-Disease Association (GDA) extraction. The dataset consists of three text files, corresponding to train, validation, and test sets, plus an additional JSON file containing the mapping between relation names and IDs. Each record in train, validation, or test files corresponds to a single GDA extracted from a sentence. Records are represented as JSON objects with the following structure: text: sentence from which the GDA was extracted. relation: relation name associated with the given GDA. h: JSON object representing the gene entity, composed of: id: NCBI Entrez ID associated with the gene entity. name: NCBI official gene symbol associated with the gene entity. pos: list consisting of starting position and length of the gene mention within text. t: JSON object representing the disease entity, composed of: id: UMLS CUI associated with the disease entity. name: UMLS preferred term associated with the disease entity. pos: list consisting of starting position and length of the disease mention within text. TBGA contains over 200,000 instances and 100,000 bags. The zip file consists of one folder, named TBGA, containing the files corresponding to the dataset. If you use or extend our work, please cite the following: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-022-04646-6#citeas TBGA paper can be found at: https://rdcu.be/cKkY2 TBGA code is available at: https://github.com/GDAMining/gda-extraction