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

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


Title: MEGGASENSE - The Metagenome/Genome Annotated Sequence Natural Language Search Engine: A Platform for the Construction of Sequence Data Warehouses
Author: Gacesa, Ranko
Zucko, Jurica   orcid.org/0000-0001-7782-6503
Petursdottir, Solveig
Gudmundsdottir, Elisabet Eik
Fridjonsson, Olafur
Diminic, Janko
Long, Paul
Cullum, John   orcid.org/0000-0002-3850-8526
Hranueli, Daslav
Hreggvidsson, Gudmundur Oli
... 1 more authors Show all authors
Date: 2017-04
Language: English
Scope: 251-257
University/Institute: Háskóli Íslands
University of Iceland
School: Verkfræði- og náttúruvísindasvið (HÍ)
School of Engineering and Natural Sciences (UI)
Department: Líf- og umhverfisvísindadeild (HÍ)
Faculty of Life and Environmental Sciences (UI)
Series: Food Technology and Biotechnology;55(2)
ISSN: 1330-9862
1334-2606 (eISSN)
DOI: 10.17113/ftb.55.02.17.4749
Subject: Bioprospecting; Carbohydrate-modifying enzymes; DNA assembly; DNA rannsóknir; Líftækni
URI: https://hdl.handle.net/20.500.11815/360

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Citation:

R. Gacesa et al.: MEGGASENSE, Food Technol. Biotechnol. 55 (2) 251–257 (2017). doi:10.17113/ftb.55.02.17.4749

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.

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Creative Commons

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