AIMC Topic: Nucleotides

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iPromoter-ET: Identifying promoters and their strength by extremely randomized trees-based feature selection.

Analytical biochemistry Aug 10, 2021
Promoter is a region of DNA that determines the transcription of a particular gene. There are several σ factors in the RNA polymerase, which has the function of identifying the promoter and facilitating the binding of the RNA polymerase to the promot...
DNA Nucleotides Promoter Regions, Genetic Support Vector Machine Sequence Analysis, DNA
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Infrared Metasurface Augmented by Deep Learning for Monitoring Dynamics between All Major Classes of Biomolecules.

Advanced materials (Deerfield Beach, Fla.) Feb 22, 2021
Insights into the fascinating molecular world of biological processes are crucial for understanding diseases, developing diagnostics, and effective therapeutics. These processes are complex as they involve interactions between four major classes of b...
Nucleic Acids Infrared Rays Lab-On-A-Chip Devices Sucrose Nucleotides Liposomes Deep Learning Spectrophotometry, Infrared Proteins
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COSMO-RS-Based Descriptors for the Machine Learning-Enabled Screening of Nucleotide Analogue Drugs against SARS-CoV-2.

The journal of physical chemistry letters Oct 26, 2020
Chemical similarity-based approaches employed to repurpose or develop new treatments for emerging diseases, such as COVID-19, correlates molecular structure-based descriptors of drugs with those of a physiological counterpart or clinical phenotype. W...
Humans SARS-CoV-2 Molecular Docking Simulation Principal Component Analysis Machine Learning Pandemics COVID-19 Binding Sites Betacoronavirus Quantum Theory Pneumonia, Viral Coronavirus Infections RNA-Dependent RNA Polymerase Nucleotides RNA, Viral Drug Evaluation, Preclinical
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Frequency spectra characterization of noncoding human genomic sequences.

Genes & genomics Aug 31, 2020
BACKGROUND: Noncoding sequences have been demonstrated to possess regulatory functions. Its classification is challenging because they do not show well-defined nucleotide patterns that can correlate with their biological functions. Genomic signal pro...
Genome, Human Regulatory Sequences, Nucleic Acid Genomics Nucleotides Humans Machine Learning Algorithms
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Predicting host taxonomic information from viral genomes: A comparison of feature representations.

PLoS computational biology May 26, 2020
The rise in metagenomics has led to an exponential growth in virus discovery. However, the majority of these new virus sequences have no assigned host. Current machine learning approaches to predicting virus host interactions have a tendency to focus...
Genome, Viral Viruses Caudovirales Nucleotides Metagenomics Sequence Analysis, DNA Linear Models Algorithms Area Under Curve Databases, Factual Phylogeny Bacteria Computational Biology Support Vector Machine
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Depression phenotype identified by using single nucleotide exact amplicon sequence variants of the human gut microbiome.

Molecular psychiatry Jan 27, 2020
Single nucleotide exact amplicon sequence variants (ASV) of the human gut microbiome were used to evaluate if individuals with a depression phenotype (DEPR) could be identified from healthy reference subjects (NODEP). Microbial DNA in stool samples o...
Humans Machine Learning Phenotype RNA, Ribosomal, 16S Nucleotides High-Throughput Nucleotide Sequencing Depression Gastrointestinal Microbiome
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Effective machine-learning assembly for next-generation amplicon sequencing with very low coverage.

BMC bioinformatics Dec 11, 2019
BACKGROUND: In short-read DNA sequencing experiments, the read coverage is a key parameter to successfully assemble the reads and reconstruct the sequence of the input DNA. When coverage is very low, the original sequence reconstruction from the read...
Base Sequence Genome, Mitochondrial Macropodidae Animals Nucleotides High-Throughput Nucleotide Sequencing Machine Learning Algorithms
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FactorNet: A deep learning framework for predicting cell type specific transcription factor binding from nucleotide-resolution sequential data.

Methods (San Diego, Calif.) Mar 26, 2019
Due to the large numbers of transcription factors (TFs) and cell types, querying binding profiles of all valid TF/cell type pairs is not experimentally feasible. To address this issue, we developed a convolutional-recurrent neural network model, call...
Neural Networks, Computer Software Nucleotides Deep Learning Binding Sites Protein Binding Chromatin Transcription Factors
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Recognition Tunneling of Canonical and Modified RNA Nucleotides for Their Identification with the Aid of Machine Learning.

ACS nano Jun 28, 2018
In the present study, we demonstrate a tunneling nanogap technique to identify individual RNA nucleotides, which can be used as a mechanism to read the nucleobases for direct sequencing of RNA in a solid-state nanopore. The tunneling nanogap is compo...
Microscopy, Scanning Tunneling Surface Properties Nanotechnology Machine Learning Nanopores Nucleotides Particle Size RNA Molecular Structure
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The folded k-spectrum kernel: A machine learning approach to detecting transcription factor binding sites with gapped nucleotide dependencies.

PloS one Oct 5, 2017
Understanding the molecular machinery involved in transcriptional regulation is central to improving our knowledge of an organism's development, disease, and evolution. The building blocks of this complex molecular machinery are an organism's genomic...
Machine Learning Support Vector Machine Transcription Factors Nucleotides Binding Sites
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