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For COGs assignment, a RPS-BLAST search was performed using the COG database [ 46, 47] and results were filtered, selecting only hits displaying e-values > 10-8.
A protein based comparative approach using the COG database as a starting point was carried out to detect new lambdoid prophage like elements in a set of completely sequenced genomes [32].
Genes were annotated with functional categories using the COG database.
All genes were annotated with functional categories, where possible, using the COG database [ 13, 14].
Unigenes were also subjected to sequence comparison using the COG database for gene function prediction [ 21].
Using the COG database, orthologous gene products can be classified, and the possible functions of unigenes can be predicted.
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Using the COGs database 48% of the B. hyodysenteriae proteins were classified into three functional groups (Table 2), and only ∼10% were assigned to the "poorly characterized" group.
The number of proteins annotated using the COGs database was slightly less than RefSeq.
Predicted proteins were functionally categorized using the COGs database [ 40], and COGs categories were compared among the genomes of GP72, Pf-5, M18, and A1501.
We clustered the orthologus groups of proteins into higher and more detailed levels of functional groups using the COGs database (Additional file 3).
We used the COGs database [ 74] to undertake functional annotation across the four broad categories and sub categories to shared regions (all strains) as well as recombinant quartets.
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using the cog homology
using the cog software
using the MicrobesOnline database
using the cog approach
using the Aria database
using the cog classification
using the Cassandra database
using the Mascot database
using the PostgreSQL database
using the Webribo database
using the cog genotyping
using the Amadeus database
using the cog construction
using the SortMeRNA database
using the ProfCom database
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