AIMC Topic: Codon
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Optimization of C-to-G base editors with sequence context preference predictable by machine learning methods.
Nature communications
Aug 12, 2021
Efficient and precise base editors (BEs) for C-to-G transversion are highly desirable. However, the sequence context affecting editing outcome largely remains unclear. Here we report engineered C-to-G BEs of high efficiency and fidelity, with the seq...
Full-length ribosome density prediction by a multi-input and multi-output model.
PLoS computational biology
Mar 26, 2021
Translation elongation is regulated by a series of complicated mechanisms in both prokaryotes and eukaryotes. Although recent advance in ribosome profiling techniques has enabled one to capture the genome-wide ribosome footprints along transcripts at...
Bringing Structural Implications and Deep Learning-Based Drug Identification for Mutants.
Journal of chemical information and modeling
Jan 29, 2021
Colorectal cancer is considered one of the leading causes of death that is linked with the Kirsten Rat Sarcoma () harboring codons 13 and 61 mutations. The objective for this study is to search for clinically important codon 61 mutations and analyze ...
Codon optimization with deep learning to enhance protein expression.
Scientific reports
Oct 19, 2020
Heterologous expression is the main approach for recombinant protein production ingenetic synthesis, for which codon optimization is necessary. The existing optimization methods are based on biological indexes. In this paper, we propose a novel codon...
DeeplyEssential: a deep neural network for predicting essential genes in microbes.
BMC bioinformatics
Sep 30, 2020
BACKGROUND: Essential genes are those genes that are critical for the survival of an organism. The prediction of essential genes in bacteria can provide targets for the design of novel antibiotic compounds or antimicrobial strategies.
Improving Protein Expression Prediction Using Extra Features and Ensemble Averaging.
PloS one
Mar 2, 2016
The article focus is the improvement of machine learning models capable of predicting protein expression levels based on their codon encoding. Support vector regression (SVR) and partial least squares (PLS) were used to create the models. SVR yields ...
On fuzzy semantic similarity measure for DNA coding.
Computers in biology and medicine
Dec 31, 2015
A coding measure scheme numerically translates the DNA sequence to a time domain signal for protein coding regions identification. A number of coding measure schemes based on numerology, geometry, fixed mapping, statistical characteristics and chemic...
Codon bias and gene ontology in holometabolous and hemimetabolous insects.
Journal of experimental zoology. Part B, Molecular and developmental evolution
Oct 26, 2015
The relationship between preferred codon use (PCU), developmental mode, and gene ontology (GO) was investigated in a sample of nine insect species with sequenced genomes. These species were selected to represent two distinct modes of insect developme...
Improved feature-based prediction of SNPs in human cytochrome P450 enzymes.
Interdisciplinary sciences, computational life sciences
Mar 21, 2015
Single nucleotide polymorphisms (SNPs) make up the most common form of mutations in human cytochrome P450 enzymes family, and have the potential to bring with different drug responses or specific diseases in individual patients. Here, based on machin...
DNA-CBIR: DNA Translation Inspired Codon Pattern-Based Deep Image Feature Extraction for Content-Based Image Retrieval.
IEEE transactions on nanobioscience
Jul 1, 2025
DNA is emerging as a promising medium for storing huge volumes of data in a confined space that remains intact for thousands of years. Although this technique is very efficient, especially for multimedia data like images, there is a lack of efficient...
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