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This paper presents a comparison of two lateral guidance strategies based on the CoG and on the CoP using the same control strategy.
Tables 3 and 4 further validate these conclusions by showing the ranking of alternative priorities based on the COG and Chen's defuzzification methods, respectively.
These ORFs were grouped into 11 classes based on the COG classification.
Our genome comparisons are based on the COG database (3 Eukarya, 13 Archaea, 50 Bacteria) and in addition six myxobacterial and two actinobacterial genomes (Table S1).
The functional classification of core, distributed and strain-specific genes as identified by mCGH was based on the COG classification scheme [68].
Based on the COG and Gene Ontology (GO), 593 unique sequences were classified.
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On the one hand, the assessment is based on the cogging torque fluctuations.
Genes encoding conserved secretion machinery-related proteins were identified based on the COGs (Clusters of Orthologous Groups) annotations, and are listed in Additional File 1.
The distribution of the differentially expressed genes and proteins over the different Clusters of Orthologous Groups (COG) categories (based on the NCBI-COG database of P. putida KT2440 (http://www.ncbi.nlm.nih.gov/sutils/coxik.cgi gi=266)) was very similar for glucose and glycerol-grown P. putida S12palB1 (Fig. 2a, b).
KOG functional classification, Gene Ontology (GO) and pathway annotation and enrichment analyses were based on the NCBI COG (https://www.ncbi.nlm.nih.gov/COG/), Gene Ontology Database (http://www.geneontology.org/) and KEGG pathway database (http://www.genome.jp/kegg/), respectively.
As described in the previous sections, Figure 6 recapitulates our observation that the two groups of selected metagenomes: lignocellulolytic and non-lignocellulolytic, are hardly distinguishable based on the taxonomic, COG, or KEGG profiles.
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