ArticleNucleic acids research2014
The Structure-Function Linkage Database.
Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 149 papers.
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Who cites it
149 citing papers in PubMed.
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- Chromosome-level genome assembly of Cryptosporidium parvum by long-read sequencing of ten oocysts.Scientific data · 2024Article
- Bioinformatics analysis of the Microsporidia sp. MB genome: a malaria transmission-blocking symbiont of the Anopheles arabiensis mosquito.BMC genomics · 2024Article
- A comprehensive review and comparison of existing computational methods for protein function prediction.Briefings in bioinformatics · 2024Review
- Interpreting Gene Ontology Annotations Derived from Sequence Homology Methods.Methods in molecular biology (Clifton, N.J.) · 2024Article
- A metagenomic library cloning strategy that promotes high-level expression of captured genes to enable efficient functional screening.Cell chemical biology · 2023Article
89 more citing papers are in PubMed but not listed here.
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Authors and funding
19 authors.
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Abstract
The Structure-Function Linkage Database (SFLD, http://sfld.rbvi.ucsf.edu/) is a manually curated classification resource describing structure-function relationships for functionally diverse enzyme superfamilies. Members of such superfamilies are diverse in their overall reactions yet share a common ancestor and some conserved active site features associated with conserved functional attributes such as a partial reaction. Thus, despite their different functions, members of these superfamilies 'look alike', making them easy to misannotate. To address this complexity and enable rational transfer of functional features to unknowns only for those members for which we have sufficient functional information, we subdivide superfamily members into subgroups using sequence information, and lastly into families, sets of enzymes known to catalyze the same reaction using the same mechanistic strategy. Browsing and searching options in the SFLD provide access to all of these levels. The SFLD offers manually curated as well as automatically classified superfamily sets, both accompanied by search and download options for all hierarchical levels. Additional information includes multiple sequence alignments, tab-separated files of functional and other attributes, and sequence similarity networks. The latter provide a new and intuitively powerful way to visualize functional trends mapped to the context of sequence similarity.
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