AIMC Topic: Nucleotides
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Loop Nucleotide Chemical Shifts as a Tool to Characterize DNA G-Quadruplexes.
Chemphyschem : a European journal of chemical physics and physical chemistry
May 7, 2025
DNA G-quadruplexes are known to play myriad functional roles in the cellular context and their structural diversity has diverse applications in various fields of science. Solution-state NMR spectroscopy has been instrumental in characterization of DN...
Exploring species taxonomic kingdom using information entropy and nucleotide compositional features of coding sequences based on machine learning methods.
Methods (San Diego, Calif.)
Apr 23, 2025
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...
Machine Learning-Driven Quantum Sequencing of Natural and Chemically Modified DNA.
ACS applied materials & interfaces
Mar 29, 2025
Simultaneous identification of natural and chemically modified DNA nucleotides at molecular resolution remains a pivotal challenge in genomic science. Despite significant advances in current sequencing technologies, the ability to identify subtle cha...
Integrating machine learning and multi-omics analysis to reveal nucleotide metabolism-related immune genes and their functional validation in ischemic stroke.
Frontiers in immunology
Mar 26, 2025
BACKGROUND: Ischemic stroke (IS) is a major global cause of death and disability, linked to nucleotide metabolism imbalances. This study aimed to identify nucleotide metabolism-related genes associated with IS and explore their roles in disease mecha...
Identifying Protein-Nucleotide Binding Residues via Grouped Multi-task Learning and Pre-trained Protein Language Models.
Journal of chemical information and modeling
Jan 9, 2025
The accurate identification of protein-nucleotide binding residues is crucial for protein function annotation and drug discovery. Numerous computational methods have been proposed to predict these binding residues, achieving remarkable performance. H...
Effect of graphene electrode functionalization on machine learning-aided single nucleotide classification.
Nanoscale
Nov 7, 2024
Solid-state nanogap-based DNA sequencing with a quantum tunneling approach has emerged as a promising avenue due to its potential to deliver swift and precise sequencing outcomes. Nevertheless, despite significant progress, experimentally achieving s...
Cross-Species Prediction of Transcription Factor Binding by Adversarial Training of a Novel Nucleotide-Level Deep Neural Network.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Jul 30, 2024
Cross-species prediction of TF binding remains a major challenge due to the rapid evolutionary turnover of individual TF binding sites, resulting in cross-species predictive performance being consistently worse than within-species performance. In thi...
Precision Basecalling of Single DNA Nucleotide from Overlapped Transmission Readouts with Machine Learning Aided Solid-State Nanogap.
ACS applied materials & interfaces
May 31, 2024
DNA sequencing with the quantum tunneling technique heralds a paradigm shift in genetic analysis, promising rapid and accurate identification for diverging applications ranging from personalized medicine to security issues. However, the widespread di...
Utilizing genomic signatures to gain insights into the dynamics of SARS-CoV-2 through Machine and Deep Learning techniques.
BMC bioinformatics
Mar 27, 2024
The global spread of the SARS-CoV-2 pandemic, originating in Wuhan, China, has had profound consequences on both health and the economy. Traditional alignment-based phylogenetic tree methods for tracking epidemic dynamics demand substantial computati...
GeneAI 3.0: powerful, novel, generalized hybrid and ensemble deep learning frameworks for miRNA species classification of stationary patterns from nucleotides.
Scientific reports
Mar 26, 2024
Due to the intricate relationship between the small non-coding ribonucleic acid (miRNA) sequences, the classification of miRNA species, namely Human, Gorilla, Rat, and Mouse is challenging. Previous methods are not robust and accurate. In this study,...
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