Restructured GEO: restructuring Gene Expression Omnibus metadata for genome dynamics analysis

• DOI: 10.1093/database/bay145
• Publication Date: 2018-12-29T15:08:23Z
• Authors: Guocai Chen; Juan Camilo Ramírez; Nan Deng; Xing Qiu; Canglin Wu; W Jim Zheng; Hulin Wu
• Keywords: Restructuring

Gene Expression Omnibus (GEO) and other publicly available data store their metadata in the format of unstructured English text, which is very difficult for automated reuse.We employed text mining techniques to analyze GEO developed Restructured database (ReGEO). ReGEO reorganizes categorizes series makes them searchable by two new attributes extracted automatically from each series' metadata. These are number time points tested experiment disease being investigated. also GEO, such as platform organism, type, associated PubMed ID well general keywords study's description. Our approach greatly expands usability data, demonstrating a credible improve utility vast amount era Big Data research.