AIMC Topic: DNA

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Automating the Illumina DNA library preparation kit for whole genome sequencing applications on the flowbot ONE liquid handler robot.

Scientific reports Apr 8, 2024
Whole-genome sequencing (WGS) is currently making its transition from research tool into routine (clinical) diagnostic practice. The workflow for WGS includes the highly labor-intensive library preparations (LP), one of the most critical steps in the...
High-Throughput Nucleotide Sequencing Gene Library Workflow Whole Genome Sequencing Reproducibility of Results Lipopolysaccharides Robotics DNA Humans
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DNA Family: Boosting Weight-Sharing NAS With Block-Wise Supervisions.

IEEE transactions on pattern analysis and machine intelligence Apr 3, 2024
Neural Architecture Search (NAS), aiming at automatically designing neural architectures by machines, has been considered a key step toward automatic machine learning. One notable NAS branch is the weight-sharing NAS, which significantly improves sea...
Plant Extracts DNA Machine Learning Algorithms
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Integrative analysis with machine learning identifies diagnostic and prognostic signatures in neuroblastoma based on differentially DNA methylated enhancers between INSS stage 4 and 4S neuroblastoma.

Journal of cancer research and clinical oncology Mar 21, 2024
INTRODUCTION: Accumulating evidence demonstrates that aberrant methylation of enhancers is crucial in gene expression profiles across several cancers. However, the latent effect of differently expressed enhancers between INSS stage 4S and 4 neuroblas...
Calcium-Binding Proteins Neuroblastoma Trans-Activators Forkhead Transcription Factors Prognosis Humans Risk Factors Tumor Microenvironment Machine Learning DNA
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EPDRNA: A Model for Identifying DNA-RNA Binding Sites in Disease-Related Proteins.

The protein journal Mar 16, 2024
Protein-DNA and protein-RNA interactions are involved in many biological processes and regulate many cellular functions. Moreover, they are related to many human diseases. To understand the molecular mechanism of protein-DNA binding and protein-RNA b...
RNA-Binding Proteins Databases, Protein Protein Binding Computational Biology RNA Binding Sites DNA DNA-Binding Proteins Humans Machine Learning Algorithms
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Prediction of DNA origami shape using graph neural network.

Nature materials Mar 14, 2024
Unlike proteins, which have a wealth of validated structural data, experimentally or computationally validated DNA origami datasets are limited. Here we present a graph neural network that can predict the three-dimensional conformation of DNA origami...
Nucleic Acid Conformation Neural Networks, Computer DNA
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DeepSF-4mC: A deep learning model for predicting DNA cytosine 4mC methylation sites leveraging sequence features.

Computers in biology and medicine Feb 16, 2024
N-methylcytosine (4mC) is a DNA modification involving the addition of a methyl group to the fourth nitrogen atom of the cytosine base. This modification may influence gene regulation, providing potential insights into gene control mechanisms. Tradit...
Artificial Intelligence Deep Learning Cytosine DNA Methylation DNA
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RUBICON: a framework for designing efficient deep learning-based genomic basecallers.

Genome biology Feb 16, 2024
Nanopore sequencing generates noisy electrical signals that need to be converted into a standard string of DNA nucleotide bases using a computational step called basecalling. The performance of basecalling has critical implications for all later step...
Nanopores DNA Deep Learning Nucleotides Genomics Sequence Analysis, DNA
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Building an ab initio solvated DNA model using Euclidean neural networks.

PloS one Feb 15, 2024
Accurately modeling large biomolecules such as DNA from first principles is fundamentally challenging due to the steep computational scaling of ab initio quantum chemistry methods. This limitation becomes even more prominent when modeling biomolecule...
DNA Neural Networks, Computer Solvents
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Predicting DNA structure using a deep learning method.

Nature communications Feb 9, 2024
Understanding the mechanisms of protein-DNA binding is critical in comprehending gene regulation. Three-dimensional DNA structure, also described as DNA shape, plays a key role in these mechanisms. In this study, we present a deep learning-based meth...
Machine Learning Deep Learning Protein Binding Proteins DNA
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promSEMBLE: Hard Pattern Mining and Ensemble Learning for Detecting DNA Promoter Sequences.

IEEE/ACM transactions on computational biology and bioinformatics Feb 5, 2024
Accurate identification of DNA promoter sequences is of crucial importance in unraveling the underlying mechanisms that regulate gene transcription. Initiation of transcription is controlled through regulatory transcription factors binding to promote...
Transcription, Genetic TATA Box Machine Learning Base Sequence Promoter Regions, Genetic DNA
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