AIMC Topic: Sequence Analysis, DNA

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Comprehensive benchmark and architectural analysis of deep learning models for nanopore sequencing basecalling.

Genome biology Apr 11, 2023
BACKGROUND: Nanopore-based DNA sequencing relies on basecalling the electric current signal. Basecalling requires neural networks to achieve competitive accuracies. To improve sequencing accuracy further, new models are continuously proposed with new...
Sequence Analysis, DNA Nanopore Sequencing Neural Networks, Computer Deep Learning
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A Method for Predicting DNA Motif Length Based On Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2023
A DNA motif is a sequence pattern shared by the DNA sequence segments that bind to a specific protein. Discovering motifs in a given DNA sequence dataset plays a vital role in studying gene expression regulation. As an important attribute of the DNA ...
Sequence Analysis, DNA Nucleotide Motifs Algorithms Deep Learning Neural Networks, Computer
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Detecting genomic deletions from high-throughput sequence data with unsupervised learning.

BMC bioinformatics Jan 27, 2023
BACKGROUND: Structural variation (SV), which ranges from 50 bp to [Formula: see text] 3 Mb in size, is an important type of genetic variations. Deletion is a type of SV in which a part of a chromosome or a sequence of DNA is lost during DNA replicati...
Humans Software High-Throughput Nucleotide Sequencing Sequence Analysis, DNA Genome, Human Genomic Structural Variation Genomics Unsupervised Machine Learning
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Operon Finder: A Deep Learning-based Web Server for Accurate Prediction of Prokaryotic Operons.

Journal of molecular biology Dec 14, 2022
Operons are groups of consecutive genes that transcribe together under the regulation of a common promoter. They influence protein regulation and various physiological pathways, making their accurate detection desirable. The detection of operons thro...
Internet Genome, Bacterial Sequence Analysis, DNA Operon Prokaryotic Cells Humans Software Algorithms Deep Learning
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RMSCNN: A Random Multi-Scale Convolutional Neural Network for Marine Microbial Bacteriocins Identification.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2022
The abuse of traditional antibiotics has led to an increase in the resistance of bacteria and viruses. Similar to the function of antibacterial peptides, bacteriocins are more common as a kind of peptides produced by bacteria that have bactericidal o...
Aquatic Organisms Bacteriocins Sequence Analysis, DNA Anti-Bacterial Agents Peptides Neural Networks, Computer Drug Discovery Bacteria
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Minimum Functional Length Analysis of K-Mer Based on BPNN.

IEEE/ACM transactions on computational biology and bioinformatics Oct 10, 2022
BP neural network (BPNN), as a multilayer feed-forward network, can realize the deep cognition to target data and high accuracy to output results. However, there were still no related research of k-mer based on BPNN yet. In present study, BPNN was us...
Algorithms Sequence Analysis, DNA Base Sequence Nucleic Acids Neural Networks, Computer
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Using Artificial Neural Networks to Model Errors in Biochemical Manipulation of DNA Molecules.

IEEE/ACM transactions on computational biology and bioinformatics Oct 10, 2022
In recent years, the non-biological applications of DNA molecules have made considerable progress; most of these applications were performed in vitro, involving biochemical operations such as synthesis, amplification and sequencing. Because errors ma...
DNA Neural Networks, Computer Sequence Analysis, DNA
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SVision: a deep learning approach to resolve complex structural variants.

Nature methods Sep 16, 2022
Complex structural variants (CSVs) encompass multiple breakpoints and are often missed or misinterpreted. We developed SVision, a deep-learning-based multi-object-recognition framework, to automatically detect and haracterize CSVs from long-read sequ...
Genome Deep Learning High-Throughput Nucleotide Sequencing Sequence Analysis, DNA
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Automated filtering of genome-wide large deletions through an ensemble deep learning framework.

Methods (San Diego, Calif.) Aug 28, 2022
Computational methods based on whole genome linked-reads and short-reads have been successful in genome assembly and detection of structural variants (SVs). Numerous variant callers that rely on linked-reads and short reads can detect genetic variati...
Humans Deep Learning Genome, Human High-Throughput Nucleotide Sequencing Sequence Analysis, DNA Base Sequence Sequence Analysis
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DeepBarcoding: Deep Learning for Species Classification Using DNA Barcoding.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2022
DNA barcodes with short sequence fragments are used for species identification. Because of advances in sequencing technologies, DNA barcodes have gradually been emphasized. DNA sequences from different organisms are easily and rapidly acquired. There...
DNA DNA Barcoding, Taxonomic Deep Learning Neural Networks, Computer Sequence Analysis, DNA
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