AIMC Topic: Codon

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Conditional deep learning model reveals translation elongation determinants during amino acid deprivation.

Communications biology
Translation elongation plays a key role in cellular homeostasis, and dysregulation of this process has been implicated in various diseases and metabolic disorders. Uncovering the causes of intragenic heterogeneity of translation, especially in contex...

Structural and functional analysis of the accessory gene regulators of Staphylococcus aureus and Staphylococcus epidermidis: an in Silico approach.

BMC microbiology
BACKGROUND: Staphylococcus aureus and Staphylococcus epidermidis are tenacious pathogens that cause toxic shock syndrome. Accessory gene regulator (Agr) of Staphylococcus sp. controls the expression of multiple genes that encode virulence properties....

Exploring species taxonomic kingdom using information entropy and nucleotide compositional features of coding sequences based on machine learning methods.

Methods (San Diego, Calif.)
The flow of genetic information from DNA to protein is governed by the central dogma of molecular biology. Genetic drift and mutations usually lead to changes in DNA composition, thereby affecting the coding sequences (CDS) that encode functional pro...

Predicting viral host codon fitness and path shifting through tree-based learning on codon usage biases and genomic characteristics.

Scientific reports
Viral codon fitness (VCF) of the host and the VCF shifting has seldom been studied under quantitative measurements, although they could be concepts vital to understand pathogen epidemiology. This study demonstrates that the relative synonymous codon ...

CodonTransformer: a multispecies codon optimizer using context-aware neural networks.

Nature communications
Degeneracy in the genetic code allows many possible DNA sequences to encode the same protein. Optimizing codon usage within a sequence to meet organism-specific preferences faces combinatorial explosion. Nevertheless, natural sequences optimized thro...

Predicting lncRNA-protein interactions using a hybrid deep learning model with dinucleotide-codon fusion feature encoding.

BMC genomics
Long non-coding RNAs (lncRNAs) play crucial roles in numerous biological processes and are involved in complex human diseases through interactions with proteins. Accurate identification of lncRNA-protein interactions (LPI) can help elucidate the func...

Differentially used codons among essential genes in bacteria identified by machine learning-based analysis.

Molecular genetics and genomics : MGG
Codon usage bias (CUB), the uneven usage of synonymous codons encoding the same amino acid, differs among genes within and across bacteria genomes. CUB is known to be influenced by gene expression and accordingly, CUB differs between the high-express...

Riboformer: a deep learning framework for predicting context-dependent translation dynamics.

Nature communications
Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurements of translation at the genome scale. How...

Machine learning classifiers predict key genomic and evolutionary traits across the kingdoms of life.

Scientific reports
In this study, we investigate how an organism's codon usage bias can serve as a predictor and classifier of various genomic and evolutionary traits across the domains of life. We perform secondary analysis of existing genetic datasets to build severa...

Using Machine Learning for Predicting the Effect of Mutations in the Initiation Codon.

IEEE journal of biomedical and health informatics
The effect of mutations has been traditionally predicted by studying what may happen due to the substitution of one amino acid for another one. This approach may be effective for mutations with impact in the function of the protein, but ineffective f...