Gao Ge's research group has made progress in the integration and analysis of non-coding variants related to human regulation

Although 97% of the regions in the human genome do not encode proteins, they still have functions that cannot be ignored.

Recently, Peking University Biomedical Frontier Innovation Center (BIOPIC), Beijing Future Gene Diagnosis Advanced Innovation Center (ICG), Peking University School of Life Sciences Bioinformatics Center (CBI), State Key Laboratory of Protein and Plant Gene Research Gao Ge Group Through the collection and integration of data generated by multiple large-scale experiments to verify expression regulation mutation experiments, the human high-quality expression regulation-related non-coding mutation database REVA was constructed, and the performance of 7 mainstream non-coding mutation prediction tools was further evaluated

Through systematic mining and integration of published literature, the author extracted and collected more than 11.

Figure 1: Overview of the structure of the REVA database and partial results of the tool evaluation

At present, the REVA database has been officially released online ( http://reva.

Doctoral students Wang Yu and Shi Fangyuan from the School of Life Sciences of Peking University are the co-first authors of the paper, researcher Gao Ge is the corresponding author, and Liang Yu, a master of the School of Life Sciences of Nanchang University, provided strong support in data collection

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