Building a text-mining-based post-translational modification (PTM) database for SUMOylation

Client’s requirement

A biotech company, based out of the US, partnered with Excelra to develop an integrated database for SUMOylation-a post-translational event of interest-from publicly available databases and literature.

The client wanted to integrate all publicly available data with internal information pertaining to the post-translational modification of their interest (SUMOylation) into a structured format. The data for SUMOylation is very scattered and must be collated and standardized prior to any landscape analysis or target identification. We were engaged to collate information, standardize it, and develop the lexicon.

Our approach

Excelra’s curation environment ensures seamless, quality-assured curation of biomedical data. For the pilot stage of this project, 100 free full-text articles spanning around 22 SUMOylation-mediating enzymes were identified from PubMed central. Article identification was completed using Excelra’s literature-mining algorithm and SUMOylation lexicon.

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