Title |
FALDO: a semantic standard for describing the location of nucleotide and protein feature annotation
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Published in |
Journal of Biomedical Semantics, June 2016
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DOI | 10.1186/s13326-016-0067-z |
Pubmed ID | |
Authors |
Jerven T. Bolleman, Christopher J. Mungall, Francesco Strozzi, Joachim Baran, Michel Dumontier, Raoul J. P. Bonnal, Robert Buels, Robert Hoehndorf, Takatomo Fujisawa, Toshiaki Katayama, Peter J. A. Cock |
Abstract |
Nucleotide and protein sequence feature annotations are essential to understand biology on the genomic, transcriptomic, and proteomic level. Using Semantic Web technologies to query biological annotations, there was no standard that described this potentially complex location information as subject-predicate-object triples. We have developed an ontology, the Feature Annotation Location Description Ontology (FALDO), to describe the positions of annotated features on linear and circular sequences. FALDO can be used to describe nucleotide features in sequence records, protein annotations, and glycan binding sites, among other features in coordinate systems of the aforementioned "omics" areas. Using the same data format to represent sequence positions that are independent of file formats allows us to integrate sequence data from multiple sources and data types. The genome browser JBrowse is used to demonstrate accessing multiple SPARQL endpoints to display genomic feature annotations, as well as protein annotations from UniProt mapped to genomic locations. Our ontology allows users to uniformly describe - and potentially merge - sequence annotations from multiple sources. Data sources using FALDO can prospectively be retrieved using federalised SPARQL queries against public SPARQL endpoints and/or local private triple stores. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 5 | 24% |
Switzerland | 3 | 14% |
Japan | 2 | 10% |
United Kingdom | 1 | 5% |
Ghana | 1 | 5% |
Unknown | 9 | 43% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 17 | 81% |
Scientists | 4 | 19% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United States | 5 | 9% |
Japan | 2 | 3% |
Canada | 2 | 3% |
Italy | 1 | 2% |
Brazil | 1 | 2% |
Sweden | 1 | 2% |
Spain | 1 | 2% |
Unknown | 45 | 78% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 20 | 34% |
Professor > Associate Professor | 9 | 16% |
Student > Ph. D. Student | 8 | 14% |
Student > Master | 5 | 9% |
Other | 4 | 7% |
Other | 6 | 10% |
Unknown | 6 | 10% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 26 | 45% |
Biochemistry, Genetics and Molecular Biology | 10 | 17% |
Computer Science | 8 | 14% |
Engineering | 2 | 3% |
Chemistry | 1 | 2% |
Other | 1 | 2% |
Unknown | 10 | 17% |