Title: | MEGGASENSE - The Metagenome/Genome Annotated Sequence Natural Language Search Engine: A Platform for the Construction of Sequence Data Warehouses |
Author: |
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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 |
Citation:R. Gacesa et al.: MEGGASENSE, Food Technol. Biotechnol. 55 (2) 251–257 (2017). doi:10.17113/ftb.55.02.17.4749
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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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Rights:Creative Commons
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