ArticleDatabase : the journal of biological databases and curation2018
SDADB: a functional annotation database of protein structural domains.
Article in Database : the journal of biological databases and curation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Decoding extremophiles: insights from bioinformatics, machine learning, and data-driven approaches.Briefings in bioinformatics · 2026Review
- Protein structural domain-disease association prediction based on heterogeneous networks.BMC genomics · 2025Article
- Evolution of intrinsic disorder in the structural domains of viral and cellular proteomes.Scientific reports · 2025Article
- Evolution of Intrinsic Disorder in Protein Loops.Life (Basel, Switzerland) · 2023Article
- The origin and evolution of viruses inferred from fold family structure.Archives of virology · 2020Review
- MADOKA: an ultra-fast approach for large-scale protein structure similarity searching.BMC bioinformatics · 2019Article
- MultiSourcDSim: an integrated approach for exploring disease similarity.BMC medical informatics and decision making · 2019Article
- Predicting Gene Ontology Function of Human MicroRNAs by Integrating Multiple Networks.Frontiers in genetics · 2019Article
- Integrating Multiple Interaction Networks for Gene Function Inference.Molecules (Basel, Switzerland) · 2018Article
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3 authors.
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Abstract
Annotating functional terms with individual domains is essential for understanding the functions of full-length proteins. We describe SDADB, a functional annotation database for structural domains. SDADB provides associations between gene ontology (GO) terms and SCOP domains calculated with an integrated framework. GO annotations are assigned probabilities of being correct, which are estimated with a Bayesian network by taking advantage of structural neighborhood mappings, SCOP-InterPro domain mapping information, position-specific scoring matrices (PSSMs) and sequence homolog features, with the most substantial contribution coming from high-coverage structure-based domain-protein mappings. The domain-protein mappings are computed using large-scale structure alignment. SDADB contains ontological terms with probabilistic scores for more than 214 000 distinct SCOP domains. It also provides additional features include 3D structure alignment visualization, GO hierarchical tree view, search, browse and download options.Database URL: http://sda.denglab.org.
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