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Sequence Analysis, DNA

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Classification of DNA Sequence Based on a Non-gradient Algorithm: Pseudoinverse Learners.

Methods in molecular biology (Clifton, N.J.)
This chapter proposes a prototype-based classification approach for analyzing DNA barcodes that uses a spectral representation of DNA sequences and a non-gradient neural network. Biological sequences can be viewed as data components with higher non-f...

Using a hybrid neural network architecture for DNA sequence representation: A study on N-methylcytosine sites.

Computers in biology and medicine
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...

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
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...

Precision Basecalling of Single DNA Nucleotide from Overlapped Transmission Readouts with Machine Learning Aided Solid-State Nanogap.

ACS applied materials & interfaces
DNA sequencing with the quantum tunneling technique heralds a paradigm shift in genetic analysis, promising rapid and accurate identification for diverging applications ranging from personalized medicine to security issues. However, the widespread di...

Assessment and classification of COVID-19 DNA sequence using pairwise features concatenation from multi-transformer and deep features with machine learning models.

SLAS technology
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 ...

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
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...

Fundamentals for predicting transcriptional regulations from DNA sequence patterns.

Journal of human genetics
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 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
OBJECTIVE: To integrate an enhanced molecular diagnostic technique to develop and validate a machine-learning model for diagnosing sepsis.

Ense-i6mA: Identification of DNA N-Methyladenine Sites Using XGB-RFE Feature Selection and Ensemble Machine Learning.

IEEE/ACM transactions on computational biology and bioinformatics
DNA N-methyladenine (6mA) is an important epigenetic modification that plays a vital role in various cellular processes. Accurate identification of the 6mA sites is fundamental to elucidate the biological functions and mechanisms of modification. How...

Transcription Factor Binding Site Prediction Using CnNet Approach.

IEEE/ACM transactions on computational biology and bioinformatics
Controlling the gene expression is the most important development in a living organism, which makes it easier to find different kinds of diseases and their causes. It's very difficult to know what factors control the gene expression. Transcription Fa...