AIMC Topic: DNA

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BERT6mA: prediction of DNA N6-methyladenine site using deep learning-based approaches.

Briefings in bioinformatics Mar 10, 2022
N6-methyladenine (6mA) is associated with important roles in DNA replication, DNA repair, transcription, regulation of gene expression. Several experimental methods were used to identify DNA modifications. However, these experimental methods are cost...
Deep Learning DNA Methylation DNA Software
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Diffractive deep neural network adjoint assist or (DNA): a fast and efficient nonlinear diffractive neural network implementation.

Optics express Feb 28, 2022
The recent advent of diffractive deep neural networks or DNNs has opened new avenues for the design and optimization of multi-functional optical materials; despite the effectiveness of the DNN approach, there is a need for making these networks as we...
Neural Networks, Computer Algorithms DNA
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DeepMP: a deep learning tool to detect DNA base modifications on Nanopore sequencing data.

Bioinformatics (Oxford, England) Feb 7, 2022
MOTIVATION: DNA methylation plays a key role in a variety of biological processes. Recently, Nanopore long-read sequencing has enabled direct detection of these modifications. As a consequence, a range of computational methods have been developed to ...
Sequence Analysis, DNA DNA High-Throughput Nucleotide Sequencing Deep Learning Escherichia coli Nanopore Sequencing Nanopores Humans Software
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Detection of transcription factors binding to methylated DNA by deep recurrent neural network.

Briefings in bioinformatics Jan 17, 2022
Transcription factors (TFs) are proteins specifically involved in gene expression regulation. It is generally accepted in epigenetics that methylated nucleotides could prevent the TFs from binding to DNA fragments. However, recent studies have confir...
Binding Sites DNA-Binding Proteins Gene Expression Regulation Deep Learning Protein Binding DNA Methylation DNA Transcription Factors Humans Neural Networks, Computer Algorithms
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DeepDISOBind: accurate prediction of RNA-, DNA- and protein-binding intrinsically disordered residues with deep multi-task learning.

Briefings in bioinformatics Jan 17, 2022
Proteins with intrinsically disordered regions (IDRs) are common among eukaryotes. Many IDRs interact with nucleic acids and proteins. Annotation of these interactions is supported by computational predictors, but to date, only one tool that predicts...
Humans Neural Networks, Computer Computational Biology RNA-Binding Proteins Proteome Deep Learning Protein Binding RNA Intrinsically Disordered Proteins Nucleic Acids DNA DNA-Binding Proteins
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Deciphering the regulatory syntax of genomic DNA with deep learning.

Journal of biosciences Jan 1, 2022
An organism's genome contains many sequence regions that perform diverse functions. Examples of such regions include genes, promoters, enhancers, and binding sites for regulatory proteins and RNAs. One of biology's most important open problems is how...
Regulatory Sequences, Nucleic Acid Deep Learning Genomics DNA Promoter Regions, Genetic Enhancer Elements, Genetic
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Construction of Molecular Robots from Microtubules for Programmable Swarming.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
Swarm robotics has been attracting much attention in recent years in the field of robotics. This chapter describes a methodology for the construction of molecular swarm robots through precise control of active self-assembly of microtubules (MTs). Det...
Microtubules Computers, Molecular Robotics DNA
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Genome-wide association study-based prediction of atrial fibrillation using artificial intelligence.

Open heart Jan 1, 2022
OBJECTIVE: We previously reported early-onset atrial fibrillation (AF) associated genetic loci among a Korean population. We explored whether the AF-associated single-nucleotide polymorphisms (SNPs) selected from the Genome-Wide Association Study (GW...
Homeodomain Proteins Homeobox Protein PITX2 Artificial Intelligence Republic of Korea Humans Polymorphism, Single Nucleotide Transcription Factors Middle Aged Morbidity Female Genome-Wide Association Study Male Atrial Fibrillation DNA Genetic Predisposition to Disease
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High-performance deep learning pipeline predicts individuals in mixtures of DNA using sequencing data.

Briefings in bioinformatics Nov 5, 2021
In this study, we proposed a deep learning (DL) model for classifying individuals from mixtures of DNA samples using 27 short tandem repeats and 94 single nucleotide polymorphisms obtained through massively parallel sequencing protocol. The model was...
Deep Learning Polymorphism, Single Nucleotide Sequence Analysis, DNA DNA Humans High-Throughput Nucleotide Sequencing
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SAResNet: self-attention residual network for predicting DNA-protein binding.

Briefings in bioinformatics Sep 2, 2021
Knowledge of the specificity of DNA-protein binding is crucial for understanding the mechanisms of gene expression, regulation and gene therapy. In recent years, deep-learning-based methods for predicting DNA-protein binding from sequence data have a...
Binding Sites Protein Binding Algorithms Humans Internet DNA Computational Biology Neural Networks, Computer DNA-Binding Proteins Reproducibility of Results Deep Learning
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