ArticleNucleic acids research2010
GeMMA: functional subfamily classification within superfamilies of predicted protein structural domains.
Article in Nucleic acids research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
- Structural plasticity drives convergent evolution and functional diversification of GNAT polyamine acetyltransferases.Structure (London, England : 1993) · 2026Article
- ASMC: investigating the amino acid diversity of enzyme active sites.Bioinformatics (Oxford, England) · 2025Article
- Clustering protein functional families at large scale with hierarchical approaches.Protein science : a publication of the Protein Society · 2024Article
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- Multi-omics data integration analysis identifies the spliceosome as a key regulator of DNA double-strand break repair.NAR cancer · 2022Article
- Clustering FunFams using sequence embeddings improves EC purity.Bioinformatics (Oxford, England) · 2021Article
- GAPIT Version 3: Boosting Power and Accuracy for Genomic Association and Prediction.Genomics, proteomics & bioinformatics · 2021Article
- Domain-mediated interactions for protein subfamily identification.Scientific reports · 2020Article
- New computational approaches to understanding molecular protein function.PLoS computational biology · 2018Article
- Article
- Structural and Functional View of Polypharmacology.Scientific reports · 2017Article
- An overview of comparative modelling and resources dedicated to large-scale modelling of genome sequences.Acta crystallographica. Section D, Structural biology · 2017Review
- An approach to functionally relevant clustering of the protein universe: Active site profile-based clustering of protein structures and sequences.Protein science : a publication of the Protein Society · 2017Article
- An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.PLoS computational biology · 2017Article
- CATH: an expanded resource to predict protein function through structure and sequence.Nucleic acids research · 2017Article
- Biocuration in the structure-function linkage database: the anatomy of a superfamily.Database : the journal of biological databases and curation · 2017Article
- DASP3: identification of protein sequences belonging to functionally relevant groups.BMC bioinformatics · 2016Article
- Novel Computational Protocols for Functionally Classifying and Characterising Serine Beta-Lactamases.PLoS computational biology · 2016Article
- Gene3D: expanding the utility of domain assignments.Nucleic acids research · 2016Article
- Functional classification of CATH superfamilies: a domain-based approach for protein function annotation.Bioinformatics (Oxford, England) · 2015Article
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3 authors.
Funding
Abstract
GeMMA (Genome Modelling and Model Annotation) is a new approach to automatic functional subfamily classification within families and superfamilies of protein sequences. A major advantage of GeMMA is its ability to subclassify very large and diverse superfamilies with tens of thousands of members, without the need for an initial multiple sequence alignment. Its performance is shown to be comparable to the established high-performance method SCI-PHY. GeMMA follows an agglomerative clustering protocol that uses existing software for sensitive and accurate multiple sequence alignment and profile-profile comparison. The produced subfamilies are shown to be equivalent in quality whether whole protein sequences are used or just the sequences of component predicted structural domains. A faster, heuristic version of GeMMA that also uses distributed computing is shown to maintain the performance levels of the original implementation. The use of GeMMA to increase the functional annotation coverage of functionally diverse Pfam families is demonstrated. It is further shown how GeMMA clusters can help to predict the impact of experimentally determining a protein domain structure on comparative protein modelling coverage, in the context of structural genomics.
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