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High-Throughput Nucleotide Sequencing

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Identifying complex motifs in massive omics data with a variable-convolutional layer in deep neural network.

Briefings in bioinformatics
Motif identification is among the most common and essential computational tasks for bioinformatics and genomics. Here we proposed a novel convolutional layer for deep neural network, named variable convolutional (vConv) layer, for effective motif ide...

Omics big data and medical artificial intelligence.

Yi chuan = Hereditas
With the rapid development of high-throughput sequencing technology and computer science, the amount of large omics data has increased exponentially, the advantages of multi-omics analysis have gradually emerged, and the application of artificial int...

Implementing FAIR data management within the German Network for Bioinformatics Infrastructure (de.NBI) exemplified by selected use cases.

Briefings in bioinformatics
This article describes some use case studies and self-assessments of FAIR status of de.NBI services to illustrate the challenges and requirements for the definition of the needs of adhering to the FAIR (findable, accessible, interoperable and reusabl...

MSIsensor-ct: microsatellite instability detection using cfDNA sequencing data.

Briefings in bioinformatics
MOTIVATION: Microsatellite instability (MSI) is a promising biomarker for cancer prognosis and chemosensitivity. Techniques are rapidly evolving for the detection of MSI from tumor-normal paired or tumor-only sequencing data. However, tumor tissues a...

A deep learning approach for filtering structural variants in short read sequencing data.

Briefings in bioinformatics
Short read whole genome sequencing has become widely used to detect structural variants in human genetic studies and clinical practices. However, accurate detection of structural variants is a challenging task. Especially existing structural variant ...

DeepSSV: detecting somatic small variants in paired tumor and normal sequencing data with convolutional neural network.

Briefings in bioinformatics
It is of considerable interest to detect somatic mutations in paired tumor and normal sequencing data. A number of callers that are based on statistical or machine learning approaches have been developed to detect somatic small variants. However, the...

SICaRiO: short indel call filtering with boosting.

Briefings in bioinformatics
Despite impressive improvement in the next-generation sequencing technology, reliable detection of indels is still a difficult endeavour. Recognition of true indels is of prime importance in many applications, such as personalized health care, diseas...

Pretraining model for biological sequence data.

Briefings in functional genomics
With the development of high-throughput sequencing technology, biological sequence data reflecting life information becomes increasingly accessible. Particularly on the background of the COVID-19 pandemic, biological sequence data play an important r...

Increasing metadata coverage of SRA BioSample entries using deep learning-based named entity recognition.

Database : the journal of biological databases and curation
High-quality metadata annotations for data hosted in large public repositories are essential for research reproducibility and for conducting fast, powerful and scalable meta-analyses. Currently, a majority of sequencing samples in the National Center...

Noninvasive early diagnosis of intestinal diseases based on artificial intelligence in genomics and microbiome.

Journal of gastroenterology and hepatology
The maturing development in artificial intelligence (AI) and genomics has propelled the advances in intestinal diseases including intestinal cancer, inflammatory bowel disease (IBD), and irritable bowel syndrome (IBS). On the other hand, colorectal c...