AI Medical Compendium Topic

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High-Throughput Nucleotide Sequencing

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Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping.

Nature communications
Predicting effects of gene regulatory elements (GREs) is a longstanding challenge in biology. Machine learning may address this, but requires large datasets linking GREs to their quantitative function. However, experimental methods to generate such d...

A network-based computational framework to predict and differentiate functions for gene isoforms using exon-level expression data.

Methods (San Diego, Calif.)
MOTIVATION: Alternative splicing makes significant contributions to functional diversity of transcripts and proteins. Many alternatively spliced gene isoforms have been shown to perform specific biological functions under different contexts. In addit...

Jupyter notebook-based tools for building structured datasets from the Sequence Read Archive.

F1000Research
The Sequence Read Archive (SRA) is a large public repository that stores raw next-generation sequencing data from thousands of diverse scientific investigations.  Despite its promise, reuse and re-analysis of SRA data has been challenged by the heter...

Age estimation using bloodstain miRNAs based on massive parallel sequencing and machine learning: A pilot study.

Forensic science international. Genetics
Age estimation is one of the most important components in the practice of forensic science, especially for body fluids or stains at crime scenes. Recent studies have focused on the application of DNA methylation for chronological age determination in...

Multiview learning for understanding functional multiomics.

PLoS computational biology
The molecular mechanisms and functions in complex biological systems currently remain elusive. Recent high-throughput techniques, such as next-generation sequencing, have generated a wide variety of multiomics datasets that enable the identification ...

DDBJ Data Analysis Challenge: a machine learning competition to predict Arabidopsis chromatin feature annotations from DNA sequences.

Genes & genetic systems
Recently, the prospect of applying machine learning tools for automating the process of annotation analysis of large-scale sequences from next-generation sequencers has raised the interest of researchers. However, finding research collaborators with ...

The hunt for sORFs: A multidisciplinary strategy.

Experimental cell research
Growing evidence illustrates the shortcomings on the current understanding of the full complexity of the proteome. Previously overlooked small open reading frames (sORFs) and their encoded microproteins have filled important gaps, exerting their func...

Exploring the Consistency of the Quality Scores with Machine Learning for Next-Generation Sequencing Experiments.

BioMed research international
BACKGROUND: Next-generation sequencing enables massively parallel processing, allowing lower cost than the other sequencing technologies. In the subsequent analysis with the NGS data, one of the major concerns is the reliability of variant calls. Alt...

Characterization of low level viraemia in HIV-infected patients receiving boosted protease inhibitor-based antiretroviral regimens.

HIV research & clinical practice
To understand the pathogenesis of low level viraemia (LLV) in HIV-infected patients on boosted protease inhibitors (PI/b), we enrolled 34 subjects with a median HIV-RNA 79 copies/mL and followed them for 15 months. Samples for next generation sequenc...