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MEGGASENSE - The Metagenome/Genome Annotated Sequence Natural Language Search Engine: A Platform for the Construction of Sequence Data Warehouses

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dc.contributor Háskóli Íslands
dc.contributor University of Iceland
dc.contributor.author Gacesa, Ranko
dc.contributor.author Zucko, Jurica
dc.contributor.author Petursdottir, Solveig
dc.contributor.author Gudmundsdottir, Elisabet Eik
dc.contributor.author Fridjonsson, Olafur
dc.contributor.author Diminic, Janko
dc.contributor.author Long, Paul
dc.contributor.author Cullum, John
dc.contributor.author Hranueli, Daslav
dc.contributor.author Hreggvidsson, Gudmundur Oli
dc.contributor.author Starcevic, Antonio
dc.date.accessioned 2017-08-25T14:33:33Z
dc.date.available 2017-08-25T14:33:33Z
dc.date.issued 2017-04
dc.identifier.citation R. Gacesa et al.: MEGGASENSE, Food Technol. Biotechnol. 55 (2) 251–257 (2017). doi:10.17113/ftb.55.02.17.4749
dc.identifier.issn 1330-9862
dc.identifier.issn 1334-2606 (eISSN)
dc.identifier.uri https://hdl.handle.net/20.500.11815/360
dc.description.abstract The MEGGASENSE platform constructs relational databases of DNA or protein sequences. The default functional analysis uses 14 106 hidden Markov model (HMM) profiles based on sequences in the KEGG database. The Solr search engine allows sophisticated queries and a BLAST search function is also incorporated. These standard capabilities were used to generate the SCATT database from the predicted proteome of Streptomyces cattleya. The implementation of a specialised metagenome database (AMYLOMICS) for bioprospecting of carbohydrate-modifying enzymes is described. In addition to standard assembly of reads, a novel ‘functional’ assembly was developed, in which screening of reads with the HMM profiles occurs before the assembly. The AMYLOMICS database incorporates additional HMM profiles for carbohydrate-modifying enzymes and it is illustrated how the combination of HMM and BLAST analyses helps identify interesting genes. A variety of different proteome and metagenome databases have been generated by MEGGASENSE.
dc.description.sponsorship This work was supported by the European Commission FP7 (265992 to J.Z., S.K.P., O.H.F., R.G., J.D., G.O.H., D.H., A.S.), the Croatian Science Foundation (09/5 to D.H.), the German Academic Exchange Service (DAAD) and the Ministry of Science, Education and Sports, Republic of Croatia (cooperation grant to D.H. and J.C.), and King's College London, UK (to P.F.L.).
dc.format.extent 251-257
dc.language.iso en
dc.publisher Faculty of Food Technology and Biotechnology, University of Zagreb, Croatia
dc.relation info:eu-repo/grantAgreement/EC/FP7/265992
dc.relation.ispartofseries Food Technology and Biotechnology;55(2)
dc.rights info:eu-repo/semantics/openAccess
dc.subject Bioprospecting
dc.subject Carbohydrate-modifying enzymes
dc.subject DNA assembly
dc.subject DNA rannsóknir
dc.subject Líftækni
dc.title MEGGASENSE - The Metagenome/Genome Annotated Sequence Natural Language Search Engine: A Platform for the Construction of Sequence Data Warehouses
dc.type info:eu-repo/semantics/article
dcterms.license Creative Commons
dc.description.version Peer Reviewed
dc.identifier.journal Food Technology and Biotechnology
dc.identifier.doi 10.17113/ftb.55.02.17.4749
dc.contributor.department Líf- og umhverfisvísindadeild (HÍ)
dc.contributor.department Faculty of Life and Environmental Sciences (UI)
dc.contributor.school Verkfræði- og náttúruvísindasvið (HÍ)
dc.contributor.school School of Engineering and Natural Sciences (UI)


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