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Sequence Analysis, DNA

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Performance analysis of conventional and AI-based variant callers using short and long reads.

BMC bioinformatics
BACKGROUND: The accurate detection of variants is essential for genomics-based studies. Currently, there are various tools designed to detect genomic variants, however, it has always been a challenge to decide which tool to use, especially when vario...

A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing.

Nature communications
Oxford Nanopore sequencing can detect DNA methylations from ionic current signal of single molecules, offering a unique advantage over conventional methods. Additionally, adaptive sampling, a software-controlled enrichment method for targeted sequenc...

RUBICON: a framework for designing efficient deep learning-based genomic basecallers.

Genome biology
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...

MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.

BMC bioinformatics
BACKGROUND: The rapid advancement of next-generation sequencing (NGS) machines in terms of speed and affordability has led to the generation of a massive amount of biological data at the expense of data quality as errors become more prevalent. This i...

Coding genomes with gapped pattern graph convolutional network.

Bioinformatics (Oxford, England)
MOTIVATION: Genome sequencing technologies reveal a huge amount of genomic sequences. Neural network-based methods can be prime candidates for retrieving insights from these sequences because of their applicability to large and diverse datasets. Howe...

NPSV-deep: a deep learning method for genotyping structural variants in short read genome sequencing data.

Bioinformatics (Oxford, England)
MOTIVATION: Structural variants (SVs) play a causal role in numerous diseases but can be difficult to detect and accurately genotype (determine zygosity) with short-read genome sequencing data (SRS). Improving SV genotyping accuracy in SRS data, part...

PPRTGI: A Personalized PageRank Graph Neural Network for TF-Target Gene Interaction Detection.

IEEE/ACM transactions on computational biology and bioinformatics
Transcription factors (TFs) regulation is required for the vast majority of biological processes in living organisms. Some diseases may be caused by improper transcriptional regulation. Identifying the target genes of TFs is thus critical for underst...

GenCoder: A Novel Convolutional Neural Network Based Autoencoder for Genomic Sequence Data Compression.

IEEE/ACM transactions on computational biology and bioinformatics
Revolutionary advances in DNA sequencing technologies fundamentally change the nature of genomics. Today's sequencing technologies have opened into an outburst in genomic data volume. These data can be used in various applications where long-term sto...

GEMA: A Genome Exact Mapping Accelerator Based on Learned Indexes.

IEEE transactions on biomedical circuits and systems
In this article, we introduce GEMA, a genome exact mapping accelerator based on learned indexes, specifically designed for FPGA implementation. GEMA utilizes a machine learning (ML) algorithm to precisely locate the exact position of read sequences w...

iM-Seeker: a webserver for DNA i-motifs prediction and scoring via automated machine learning.

Nucleic acids research
DNA, beyond its canonical B-form double helix, adopts various alternative conformations, among which the i-motif, emerging in cytosine-rich sequences under acidic conditions, holds significant biological implications in transcription modulation and t...