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◆ Frontiers in Bioinformatics2026-08-27· Annotation

Assessment of the impact of manual curation in BioCyc

R. Caspi, B. Wilson-Mortier, L. R. Moore, J. N. Karp, D. Beesley, I.T. Paulsen, P.D. Karp

原始摘要(英文原文)· Original abstract
Introduction BioCyc is an extensive collection of databases of genomic and pathway information for microorganisms and model eukaryotes. These organismal databases integrate diverse biological data by combining computationally inferred information, data imported from other databases, and, for selected organisms, literature-based manual curation. This study investigates the magnitude and significance of annotation changes performed during the curation of 10 prokaryotic genomes to better understand the rate of erroneous annotations and the value of BioCyc curation. Methods We identified curation changes by finding cases where the annotation of the protein at the start of the curation process differed from its annotation at the end of the process. Results We found that across a sample of curated databases ( n = 10), the annotation of 6,753, or 25.6% of the proteins in the pooled protein dataset (n = 26,126) were modified. Assessment of considerable sampling fractions of these proteins found that a median of 62% (mean of 52.9%) represented functionally informative name changes, rather than stylistic annotation changes. These results were then extrapolated to total proteins with name changes with uncertainty quantified via finite population correction, indicating that most Tier 2 Biocyc PGDBs received hundreds of functionally informative name changes during manual curation. On average 363, or13% (±5.4% SD) of the proteins encoded in each genome received functionally informative annotation changes, ranging from 5.3% (Streptococcus pneumoniae D39V) to 22.7% ( Staphylococcus aureus NCTC 8325). Discussion These findings demonstrate a substantial improvement in the accuracy of manually curated BioCyc databases compared with automated annotation pipelines. This result is particularly impactful as the rate of downstream propagation of erroneous annotations across biological databases can significantly compromise scientific discovery.
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