AIMC Topic: Sequence Analysis, DNA
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Using a hybrid neural network architecture for DNA sequence representation: A study on N-methylcytosine sites.
Computers in biology and medicine
May 27, 2024
N-methylcytosine (4mC) is a modified form of cytosine found in DNA, contributing to epigenetic regulation. It exists in various genomes, including the Rosaceae family encompassing significant fruit crops like apples, cherries, and roses. Previous inv...
Assessment and classification of COVID-19 DNA sequence using pairwise features concatenation from multi-transformer and deep features with machine learning models.
SLAS technology
May 23, 2024
The 2019 novel coronavirus (renamed SARS-CoV-2, and generally referred to as the COVID-19 virus) has spread to 184 countries with over 1.5 million confirmed cases. Such a major viral outbreak demands early elucidation of taxonomic classification and ...
Development of a two-layer machine learning model for the forensic application of legal and illegal poppy classification based on sequence data.
Forensic science international. Genetics
May 22, 2024
Poppies are beneficial plants with a variety of applications, including medicinal, edible, ornamental, and industrial purposes. Some Papaver species are forensically significant plants because they contain opium, a narcotic substance. Internationally...
Fundamentals for predicting transcriptional regulations from DNA sequence patterns.
Journal of human genetics
May 10, 2024
Cell-type-specific regulatory elements, cataloged through extensive experiments and bioinformatics in large-scale consortiums, have enabled enrichment analyses of genetic associations that primarily utilize positional information of the regulatory el...
A culture-independent approach, supervised machine learning, and the characterization of the microbial community composition of coastal areas across the Bay of Bengal and the Arabian Sea.
BMC microbiology
May 10, 2024
BACKGROUND: Coastal areas are subject to various anthropogenic and natural influences. In this study, we investigated and compared the characteristics of two coastal regions, Andhra Pradesh (AP) and Goa (GA), focusing on pollution, anthropogenic acti...
A Machine learning model for predicting sepsis based on an optimized assay for microbial cell-free DNA sequencing.
Clinica chimica acta; international journal of clinical chemistry
May 4, 2024
OBJECTIVE: To integrate an enhanced molecular diagnostic technique to develop and validate a machine-learning model for diagnosing sepsis.
A signal processing and deep learning framework for methylation detection using Oxford Nanopore sequencing.
Nature communications
Feb 16, 2024
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
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...
MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.
BMC bioinformatics
Feb 7, 2024
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...
Performance analysis of conventional and AI-based variant callers using short and long reads.
BMC bioinformatics
Dec 14, 2023
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...
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