ArticleDatabase : the journal of biological databases and curation2020
EnzyMine: a comprehensive database for enzyme function annotation with enzymatic reaction chemical feature.
Article in Database : the journal of biological databases and curation, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Predicting Functional Diversity Within Enzyme Families: A Practical Perspective.Chembiochem : a European journal of chemical biology · 2026Review
- Review
- EC2Vec: A Machine Learning Method to Embed Enzyme Commission (EC) Numbers into Vector Representations.Journal of chemical information and modeling · 2025Article
- Article
- Enzyme Databases in the Era of Omics and Artificial Intelligence.International journal of molecular sciences · 2023Review
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Authors and funding
7 authors.
Funding
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Abstract
Addition of chemical structural information in enzymatic reactions has proven to be significant for accurate enzyme function prediction. However, such chemical data lack systematic feature mining and hardly exist in enzyme-related databases. Therefore, global mining of enzymatic reactions will offer a unique landscape for researchers to understand the basic functional mechanisms of natural bioprocesses and facilitate enzyme function annotation. Here, we established a new knowledge base called EnzyMine, through which we propose to elucidate enzymatic reaction features and then link them with sequence and structural annotations. EnzyMine represents an advanced database that extends enzyme knowledge by incorporating reaction chemical feature strategies, strengthening the connectivity between enzyme and metabolic reactions. Therefore, it has the potential to reveal many new metabolic pathways involved with given enzymes, as well as expand enzyme function annotation. Database URL: http://www.rxnfinder.org/enzymine/.
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Registered trials
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