AIMC Topic: Nanopore Sequencing

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Enhancing novel isoform discovery: leveraging nanopore long-read sequencing and machine learning approaches.

Briefings in functional genomics Dec 6, 2024
Long-read sequencing technologies can capture entire RNA transcripts in a single sequencing read, reducing the ambiguity in constructing and quantifying transcript models in comparison to more common and earlier methods, such as short-read sequencing...
Computational Biology Sequence Analysis, RNA Transcriptome Nanopores Nanopore Sequencing High-Throughput Nucleotide Sequencing Software Machine Learning Protein Isoforms Humans
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Precision DNA methylation typing via hierarchical clustering of Nanopore current signals and attention-based neural network.

Briefings in bioinformatics Sep 23, 2024
Decoding DNA methylation sites through nanopore sequencing has emerged as a cutting-edge technology in the field of DNA methylation research, as it enables direct sequencing of native DNA molecules without the need for prior enzymatic or chemical tre...
Nanopores DNA Nanopore Sequencing DNA Methylation Sequence Analysis, DNA Cluster Analysis Neural Networks, Computer Humans
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m6ATM: a deep learning framework for demystifying the m6A epitranscriptome with Nanopore long-read RNA-seq data.

Briefings in bioinformatics Sep 23, 2024
N6-methyladenosine (m6A) is one of the most abundant and well-known modifications in messenger RNAs since its discovery in the 1970s. Recent studies have demonstrated that m6A is involved in various biological processes, such as alternative splicing ...
Transcriptome Deep Learning Software RNA, Messenger Sequence Analysis, RNA Computational Biology RNA-Seq Humans Nanopore Sequencing Adenosine Epigenesis, Genetic Nanopores
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NanoDeep: a deep learning framework for nanopore adaptive sampling on microbial sequencing.

Briefings in bioinformatics Nov 22, 2023
Nanopore sequencers can enrich or deplete the targeted DNA molecules in a library by reversing the voltage across individual nanopores. However, it requires substantial computational resources to achieve rapid operations in parallel at read-time sequ...
Humans Nanopore Sequencing Nanopores Gene Library Genome, Bacterial Deep Learning
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Deep learning identifies A-to-I RNA edits using nanopore sequencing data.

Nature methods Jul 1, 2022
Nanopores Deep Learning High-Throughput Nucleotide Sequencing RNA Nanopore Sequencing
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[Unsupervised deep learning for identifying the O -carboxymethyl guanine by nanopore sequencing].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Feb 25, 2022
O -carboxymethyl guanine(O -CMG) is a highly mutagenic alkylation product of DNA that causes gastrointestinal cancer in organisms. Existing studies used mutant porin A (MspA) nanopore assisted by Phi29 DNA polymerase to localize it. Recently, machi...
Nanopores Nanopore Sequencing Guanine Porins Deep Learning
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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 ...
Deep Learning Humans Escherichia coli High-Throughput Nucleotide Sequencing Nanopores Software DNA Nanopore Sequencing Sequence Analysis, DNA
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