Results 51 to 60 of about 95,678 (274)

Analysis of codon usage and nucleotide composition bias in polioviruses [PDF]

open access: yes, 2011
Background Poliovirus, the causative agent of poliomyelitis, is a human enterovirus and a member of the family of Picornaviridae and among the most rapidly evolving viruses known.
Jie Zhang   +8 more
core   +1 more source

Comparative analysis of codon usage between Gossypium hirsutum and G. barbadense mitochondrial genomes

open access: yesMitochondrial DNA. Part B. Resources, 2020
Gossypium hirsutum and G. barbadense mitochondrial genomes were analyzed to understand the factors shaping codon usage. While most analyses of codon usage suggest minimal to no bias, nucleotide composition, specifically GC content, was significantly ...
Zhiwen Chen   +10 more
doaj   +1 more source

Solving the riddle of codon usage preferences: a test for translational selection [PDF]

open access: yes, 1998
Translational selection is responsible for the unequal usage of synonymous codons in protein coding genes in a wide variety of organisms. It is one of the most subtle and pervasive forces of molecular evolution, yet, establishing the underlying causes ...
A Kaminskii   +17 more
core   +3 more sources

Differences in codon bias cannot explain differences in translational power among microbes

open access: yesBMC Bioinformatics, 2005
Background Translational power is the cellular rate of protein synthesis normalized to the biomass invested in translational machinery. Published data suggest a previously unrecognized pattern: translational power is higher among rapidly growing microbes,
Dethlefsen Les, Schmidt Thomas M
doaj   +1 more source

Evolutionary pressures on the yeast transcriptome [PDF]

open access: yes, 2015
Codon usage bias (CUB) is the well known phenomenon that the frequency of synonymous codons is unequal. This is presumably the result of adaptive pressures favouring some codons over others.
Chu, Dominique, Salykin, Anton
core   +1 more source

A Codon-Pair Bias Associated With Network Interactions in Influenza A, B, and C Genomes

open access: yesFrontiers in Genetics, 2021
A new codon-pair bias present in the genomes of different types of influenza virus is described. Codons with fewer network interactions are more frequency paired together than other codon-pairs in influenza A, B, and C genomes.
Ewan P. Plant, Zhiping Ye
doaj   +1 more source

Species based synonymous codon usage in fusion protein gene of Newcastle disease virus. [PDF]

open access: yesPLoS ONE, 2014
Newcastle disease is highly pathogenic to poultry and many other avian species. However, the Newcastle disease virus (NDV) has also been reported from many non-avian species.
Chandra Shekhar Kumar, Sachin Kumar
doaj   +1 more source

Genetic attenuation of ALDH1A1 increases metastatic potential and aggressiveness in colorectal cancer

open access: yesMolecular Oncology, EarlyView.
Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova   +25 more
wiley   +1 more source

PLIT: An alignment-free computational tool for identification of long non-coding RNAs in plant transcriptomic datasets [PDF]

open access: yes, 2019
Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs which play a significant role in several biological processes. RNA-seq based transcriptome sequencing has been extensively used for identification of lncRNAs.
Deshpande, Sumukh   +4 more
core   +4 more sources

Codon Bias Signatures, Organization of Microorganisms in Codon Space, and Lifestyle [PDF]

open access: yesMolecular Biology and Evolution, 2004
New and simple numerical criteria based on a codon adaptation index are applied to the complete genomic sequences of 80 Eubacteria and 16 Archaea, to infer weak and strong genome tendencies toward content bias, translational bias, and strand bias. These criteria can be applied to all microbial genomes, even those for which little biological information
Carbone, Alessandra   +2 more
openaire   +3 more sources

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