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Sequence Analysis, DNA

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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...

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...

Achieving pan-microbiome biological insights via the dbBact knowledge base.

Nucleic acids research
16S rRNA amplicon sequencing provides a relatively inexpensive culture-independent method for studying microbial communities. Although thousands of such studies have examined diverse habitats, it is difficult for researchers to use this vast trove of...

Deep-learning optimized DEOCSU suite provides an iterable pipeline for accurate ChIP-exo peak calling.

Briefings in bioinformatics
Recognizing binding sites of DNA-binding proteins is a key factor for elucidating transcriptional regulation in organisms. ChIP-exo enables researchers to delineate genome-wide binding landscapes of DNA-binding proteins with near single base-pair res...

Deep Learning on Chromatin Accessibility.

Methods in molecular biology (Clifton, N.J.)
DNA accessibility has been a powerful tool in locating active regulatory elements in a cell type, but dissecting the combinatorial logic within these regulatory elements has been a continued challenge in the field. Deep learning models have been show...

Deep learning-assisted genome-wide characterization of massively parallel reporter assays.

Nucleic acids research
Massively parallel reporter assay (MPRA) is a high-throughput method that enables the study of the regulatory activities of tens of thousands of DNA oligonucleotides in a single experiment. While MPRA experiments have grown in popularity, their small...

DeepToA: an ensemble deep-learning approach to predicting the theater of activity of a microbiome.

Bioinformatics (Oxford, England)
MOTIVATION: Metagenomics is the study of microbiomes using DNA sequencing. A microbiome consists of an assemblage of microbes that is associated with a 'theater of activity' (ToA). An important question is, to what degree does the taxonomic and funct...

DeNovoCNN: a deep learning approach to de novo variant calling in next generation sequencing data.

Nucleic acids research
De novo mutations (DNMs) are an important cause of genetic disorders. The accurate identification of DNMs from sequencing data is therefore fundamental to rare disease research and diagnostics. Unfortunately, identifying reliable DNMs remains a major...

MAMnet: detecting and genotyping deletions and insertions based on long reads and a deep learning approach.

Briefings in bioinformatics
Structural variations (SVs) play important roles in human genetic diversity; deletions and insertions are two common types of SVs that have been proven to be associated with genetic diseases. Hence, accurately detecting and genotyping SVs is signific...

LanceOtron: a deep learning peak caller for genome sequencing experiments.

Bioinformatics (Oxford, England)
MOTIVATION: Genome sequencing experiments have revolutionized molecular biology by allowing researchers to identify important DNA-encoded elements genome wide. Regions where these elements are found appear as peaks in the analog signal of an assay's ...