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Sequence Analysis, DNA

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PlasmidHunter: accurate and fast prediction of plasmid sequences using gene content profile and machine learning.

Briefings in bioinformatics
Plasmids are extrachromosomal DNA found in microorganisms. They often carry beneficial genes that help bacteria adapt to harsh conditions. Plasmids are also important tools in genetic engineering, gene therapy, and drug production. However, it can be...

Utilizing Deep Neural Networks to Fill Gaps in Small Genomes.

International journal of molecular sciences
With the widespread adoption of next-generation sequencing technologies, the speed and convenience of genome sequencing have significantly improved, and many biological genomes have been sequenced. However, during the assembly of small genomes, we st...

BertSNR: an interpretable deep learning framework for single-nucleotide resolution identification of transcription factor binding sites based on DNA language model.

Bioinformatics (Oxford, England)
MOTIVATION: Transcription factors are pivotal in the regulation of gene expression, and accurate identification of transcription factor binding sites (TFBSs) at high resolution is crucial for understanding the mechanisms underlying gene regulation. T...

GraphPro: An interpretable graph neural network-based model for identifying promoters in multiple species.

Computers in biology and medicine
Promoters are DNA sequences that bind with RNA polymerase to initiate transcription, regulating this process through interactions with transcription factors. Accurate identification of promoters is crucial for understanding gene expression regulation...

Generative language models on nucleotide sequences of human genes.

Scientific reports
Language models, especially transformer-based ones, have achieved colossal success in natural language processing. To be precise, studies like BERT for natural language understanding and works like GPT-3 for natural language generation are very impor...

Bioinformatics challenges for profiling the microbiome in cancer: pitfalls and opportunities.

Trends in microbiology
Increasing evidence suggests that the human microbiome plays an important role in cancer risk and treatment. Untargeted 'omics' techniques have accelerated research into microbiome-cancer interactions, supporting the discovery of novel associations a...

CSV-Filter: a deep learning-based comprehensive structural variant filtering method for both short and long reads.

Bioinformatics (Oxford, England)
MOTIVATION: Structural variants (SVs) play an important role in genetic research and precision medicine. As existing SV detection methods usually contain a substantial number of false positive calls, approaches to filter the detection results are nee...

Effect of graphene electrode functionalization on machine learning-aided single nucleotide classification.

Nanoscale
Solid-state nanogap-based DNA sequencing with a quantum tunneling approach has emerged as a promising avenue due to its potential to deliver swift and precise sequencing outcomes. Nevertheless, despite significant progress, experimentally achieving s...

An Integrated Multi-Model Framework Utilizing Convolutional Neural Networks Coupled with Feature Extraction for Identification of 4mC Sites in DNA Sequences.

Computers in biology and medicine
N4-methylcytosine (4mC) is a chemical modification that occurs on one of the four nucleotide bases in DNA and plays a vital role in DNA expression, repair, and replication. It also actively participates in the regulation of cell differentiation and g...

High-Risk Sequence Prediction Model in DNA Storage: The LQSF Method.

IEEE transactions on nanobioscience
Traditional DNA storage technologies rely on passive filtering methods for error correction during synthesis and sequencing, which result in redundancy and inadequate error correction. Addressing this, the Low Quality Sequence Filter (LQSF) was intro...