ArticleGenomics & informatics2017
Comparative Analysis of Predicted Gene Expression among Crenarchaeal Genomes.
Article in Genomics & informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed.
- The pattern of coding sequences in the chloroplast genome of Atropa belladonna and a comparative analysis with other related genomes in the nightshade family.Genomics & informatics · 2022Article
- Candidate Multi-Epitope Vaccine against Corona B.1.617 Lineage: In Silico Approach.Life (Basel, Switzerland) · 2022Article
- Signatures of optimal codon usage in metabolic genes inform budding yeast ecology.PLoS biology · 2021Article
- Reverse vaccinology approach towards the in-silico multiepitope vaccine development against SARS-CoV-2.F1000Research · 2021Article
- Codon usage pattern and predicted gene expression inGene: X · 2019Article
- A CAZyme-Rich Genome of a Taxonomically Novel Rhodophyte-Associated Carrageenolytic Marine Bacterium.Marine biotechnology (New York, N.Y.) · 2018Article
Corrections and comments
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Authors and funding
3 authors.
Funding
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Abstract
Research into new methods for identifying highly expressed genes in anonymous genome sequences has been going on for more than 15 years. We presented here an alternative approach based on modified score of relative codon usage bias to identify highly expressed genes in crenarchaeal genomes. The proposed algorithm relies exclusively on sequence features for identifying the highly expressed genes. In this study, a comparative analysis of predicted highly expressed genes in five crenarchaeal genomes was performed using the score of Modified Relative Codon Bias Strength (MRCBS) as a numerical estimator of gene expression level. We found a systematic strong correlation between Codon Adaptation Index and MRCBS. Additionally, MRCBS correlated well with other expression measures. Our study indicates that MRCBS can consistently capture the highly expressed genes.
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