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Ribosome binding site recognition using neural networks Genet. Mol. Biol.
Oliveira,Márcio Ferreira da Silva; Mendes,Daniele Quintella; Ferrari,Luciana Itida; Vasconcelos,Ana Tereza Ribeiro.
Pattern recognition is an important process for gene localization in genomes. The ribosome binding sites are signals that can help in the identification of a gene. It is difficult to find these signals in the genome through conventional methods because they are highly degenerated. Artificial Neural Networks is the approach used in this work to address this problem.
Tipo: Info:eu-repo/semantics/article Palavras-chave: Bioinformatics; Neural networks; Ribosome binding site.
Ano: 2004 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572004000400028
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Outstanding impact of soil tillage on the abundance of soil hydrolases revealed by a metagenomic approach BJM
Souza,Renata Carolini; Cantão,Maurício Egídio; Nogueira,Marco Antonio; Vasconcelos,Ana Tereza Ribeiro; Hungria,Mariangela.
ABSTRACT The soil represents the main source of novel biocatalysts and biomolecules of industrial relevance. We searched for hydrolases in silico in four shotgun metagenomes (4,079,223 sequences) obtained in a 13-year field trial carried out in southern Brazil, under the no-tillage (NT), or conventional tillage (CT) managements, with crop succession (CS, soybean/wheat), or crop rotation (CR, soybean/maize/wheat/lupine/oat). We identified 42,631 hydrolases belonging to five classes by comparing with the KEGG database, and 44,928 sequences by comparing with the NCBI-NR database. The abundance followed the order: lipases > laccases > cellulases > proteases > amylases > pectinases. Statistically significant differences were attributed to the...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Metagenome; Microbiome; Soil enzymes; Soil management; No-tillage.
Ano: 2018 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1517-83822018000400723
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