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High-Throughput Nucleotide Sequencing

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Enhancing novel isoform discovery: leveraging nanopore long-read sequencing and machine learning approaches.

Briefings in functional genomics
Long-read sequencing technologies can capture entire RNA transcripts in a single sequencing read, reducing the ambiguity in constructing and quantifying transcript models in comparison to more common and earlier methods, such as short-read sequencing...

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...

Improving the odds: Artificial intelligence and the great plate count anomaly.

Microbial biotechnology
Next-generation DNA sequencing has shown that the great plate count anomaly, that is, the difference between bacteria present in the environment and those that can be obtained in culture from that environment, is even greater and more persisting than...

Deep learning approaches for non-coding genetic variant effect prediction: current progress and future prospects.

Briefings in bioinformatics
Recent advancements in high-throughput sequencing technologies have significantly enhanced our ability to unravel the intricacies of gene regulatory processes. A critical challenge in this endeavor is the identification of variant effects, a key fact...

Highly accurate classification and discovery of microbial protein-coding gene functions using FunGeneTyper: an extensible deep learning framework.

Briefings in bioinformatics
High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an e...

Application and Comparison of Machine Learning and Database-Based Methods in Taxonomic Classification of High-Throughput Sequencing Data.

Genome biology and evolution
The advent of high-throughput sequencing technologies has not only revolutionized the field of bioinformatics but has also heightened the demand for efficient taxonomic classification. Despite technological advancements, efficiently processing and an...

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...

[CHARACTERIZATION OF THE ADAPTIVE IMMUNE REPERTOIRE USING NEXT GENERATION SEQUENCING: RECENT DISCOVERIES IN THE FIELD OF PRIMARY IMMUNODEFICIENCY, AND THE UPCOMING FUTURE].

Harefuah
A powerful adaptive immune system, which includes cellular (T lymphocytes) and humoral (B lymphocytes) immunity, depends on its ability to recognize and protect against millions of different foreign antigens. It does so through an enormous diverse ar...

Language model-based B cell receptor sequence embeddings can effectively encode receptor specificity.

Nucleic acids research
High throughput sequencing of B cell receptors (BCRs) is increasingly applied to study the immense diversity of antibodies. Learning biologically meaningful embeddings of BCR sequences is beneficial for predictive modeling. Several embedding methods ...