AIMC Topic: Base Composition
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SCP4ssd: A Serverless Platform for Nucleotide Sequence Synthesis Difficulty Prediction Using an AutoML Model.
Genes
Feb 28, 2023
DNA synthesis is widely used in synthetic biology to construct and assemble sequences ranging from short RBS to ultra-long synthetic genomes. Many sequence features, such as the GC content and repeat sequences, are known to affect the synthesis diffi...
Identification and Classification of Enhancers Using Dimension Reduction Technique and Recurrent Neural Network.
Computational and mathematical methods in medicine
Oct 18, 2020
Enhancers are noncoding fragments in DNA sequences, which play an important role in gene transcription and translation. However, due to their high free scattering and positional variability, the identification and classification of enhancers have a h...
Prediction and analysis of prokaryotic promoters based on sequence features.
Bio Systems
Aug 2, 2020
Promoter recognition is an important part of functional genomic annotation but a difficult problem. Many studies have been carried out to address this issue. However, they still cannot meet application needs. Most of the methods exhibit specificity, ...
An Intelligent Optimization Algorithm for Constructing a DNA Storage Code: NOL-HHO.
International journal of molecular sciences
Mar 22, 2020
The high density, large capacity, and long-term stability of DNA molecules make them an emerging storage medium that is especially suitable for the long-term storage of large datasets. The DNA sequences used in storage need to consider relevant const...
Decontaminating eukaryotic genome assemblies with machine learning.
BMC bioinformatics
Dec 1, 2017
BACKGROUND: High-throughput sequencing has made it theoretically possible to obtain high-quality de novo assembled genome sequences but in practice DNA extracts are often contaminated with sequences from other organisms. Currently, there are few exis...
Gene expression classification using epigenetic features and DNA sequence composition in the human embryonic stem cell line H1.
Gene
Jul 25, 2016
Epigenetic factors are known to correlate with gene expression in the existing studies. However, quantitative models that accurately classify the highly and lowly expressed genes based on epigenetic factors are currently lacking. In this study, a new...
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...
Identification of novel Xanthomonas euvesicatoria type III effector proteins by a machine-learning approach.
Molecular plant pathology
Aug 15, 2015
The Gram-negative bacterium Xanthomonas euvesicatoria (Xcv) is the causal agent of bacterial spot disease in pepper and tomato. Xcv pathogenicity depends on a type III secretion (T3S) system that delivers effector proteins into host cells to suppress...
Negative dataset selection impacts machine learning-based predictors for multiple bacterial species promoters.
Bioinformatics (Oxford, England)
Mar 29, 2025
MOTIVATION: Advances in bacterial promoter predictors based on machine learning have greatly improved identification metrics. However, existing models overlooked the impact of negative datasets, previously identified in GC-content discrepancies betwe...
An integrative machine learning strategy for improved prediction of essential genes in Escherichia coli metabolism using flux-coupled features.
Molecular bioSystems
Jul 25, 2017
Prediction of essential genes helps to identify a minimal set of genes that are absolutely required for the appropriate functioning and survival of a cell. The available machine learning techniques for essential gene prediction have inherent problems...
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