2016
DOI: 10.3389/fpls.2016.00242
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FragariaCyc: A Metabolic Pathway Database for Woodland Strawberry Fragaria vesca

Abstract: FragariaCyc is a strawberry-specific cellular metabolic network based on the annotated genome sequence of Fragaria vesca L. ssp. vesca, accession Hawaii 4. It was built on the Pathway-Tools platform using MetaCyc as the reference. The experimental evidences from published literature were used for supporting/editing existing entities and for the addition of new pathways, enzymes, reactions, compounds, and small molecules in the database. To date, FragariaCyc comprises 66 super-pathways, 488 unique pathways, 234… Show more

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Cited by 14 publications
(10 citation statements)
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References 84 publications
(134 reference statements)
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“…The species with the highest number of manual curated pathways are tomato (87 pathways), tobacco (72 pathways), potato (56 pathways), petunia (25 pathways), pepper (14 pathways) and the wild tomato species Solanum habrochaites (12 pathways). Metabolic databases with a high degree of manual curation and continuous updating are rare and mostly limited to model organisms, for instance, Arabidopsis thaliana in AraCyc ( 23 ) or species with high impacts on human nutrition ( 26 ) and health ( Supplementary Table S1 ). The latter involves two databases that focus on parasitic protozoans known to cause sleeping sickness ( Trypanosoma brucei ) and the skin affecting Leishmaniasis disease ( Leishmania major ).…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The species with the highest number of manual curated pathways are tomato (87 pathways), tobacco (72 pathways), potato (56 pathways), petunia (25 pathways), pepper (14 pathways) and the wild tomato species Solanum habrochaites (12 pathways). Metabolic databases with a high degree of manual curation and continuous updating are rare and mostly limited to model organisms, for instance, Arabidopsis thaliana in AraCyc ( 23 ) or species with high impacts on human nutrition ( 26 ) and health ( Supplementary Table S1 ). The latter involves two databases that focus on parasitic protozoans known to cause sleeping sickness ( Trypanosoma brucei ) and the skin affecting Leishmaniasis disease ( Leishmania major ).…”
Section: Resultsmentioning
confidence: 99%
“…To date, about 9400 such derivative PGDBs have been generated and made available in the BioCyc database collection ( http://biocyc.org/ ), but very few have been curated in a way that would corroborate the predicted metabolic network and integrate experimental information from the published scientific literature ( 16 , 18 ). MetaCyc has become the de-facto standard in species-specific database curation, and Pathway Tools generated and manually curated PGDBs have been created across the domains of life, including bacteria [ Escherichia coli in EcoCyc ( 21 )], fungi ( Saccharomyces cerevisiae in YeastCyc http://yeast.biocyc.org/ ), mammals [ Bos taurus in CattleCyc ( 22 )] and plants such as Arabidopsis thaliana in AraCyc ( 23 , 24 ), Medicago truncatula in MedicCyc ( 25 ), Fragaria vesca in FragariaCyc ( 26 ), Oryza sativa in RiceCyc ( 27 ) and Zea mays in MaizeCyc ( 28 ). While most PGDBs are created at the species level, this is not required and they can be generated at arbitrary levels in the taxonomic hierarchy.…”
Section: Introductionmentioning
confidence: 99%
“…Gene expression data can be further combined with other genomics data, typically metabolome, to assign putative functions to the genes. Data could be examined using visualization tools such as Pathway-Tools platform (Naithani et al, 2016) and further analysed using various statistical means such as correlation network analysis (Pillet et al, 2015). However, correlative information is by itself not sufficient to assign a function to a gene.…”
Section: What Tools Do We Have To Study the Relationships Between Genmentioning
confidence: 99%
“…These systems-level platforms such as Ensembl–Gramene (1), Phytozome (2), Kyoto Encyclopedia of Genes and Genomes (KEGG) (3), Reactome (4), Plant Reactome (5), BioCyc (6) and species-specific metabolic networks [i.e. Plant Metabolic Network (7), RiceCyc (8), MaizeCyc (9), VitisCyc (10), FragariaCyc (11), etc.] allow integration of various automated, semiautomated and/or manual biocuration pipelines, and provide researchers a user-friendly framework based on data mining, back-end data processing and biocuration.…”
Section: Introductionmentioning
confidence: 99%