AI Medical Compendium Topic

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High-Throughput Nucleotide Sequencing

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[Artificial intelligence-guided precision medicine in hematological disorders].

[Rinsho ketsueki] The Japanese journal of clinical hematology
Precision medicine in oncology uses genomic data to provide the right intervention in the right patients at the right time. For this purpose, next-generation sequencing (NGS) is an indispensable tool. However, further innovations are necessary, inclu...

SomaticSeq: An Ensemble and Machine Learning Method to Detect Somatic Mutations.

Methods in molecular biology (Clifton, N.J.)
A standard strategy to discover somatic mutations in a cancer genome is to use next-generation sequencing (NGS) technologies to sequence the tumor tissue and its matched normal (commonly blood or adjacent normal tissue) for side-by-side comparison. H...

Using Machine Learning to Identify True Somatic Variants from Next-Generation Sequencing.

Clinical chemistry
BACKGROUND: Molecular profiling has become essential for tumor risk stratification and treatment selection. However, cancer genome complexity and technical artifacts make identification of real variants a challenge. Currently, clinical laboratories r...

Machine learning meets genome assembly.

Briefings in bioinformatics
MOTIVATION: With the recent advances in DNA sequencing technologies, the study of the genetic composition of living organisms has become more accessible for researchers. Several advances have been achieved because of it, especially in the health scie...

The pan-genome of Saccharomyces cerevisiae.

FEMS yeast research
Understanding genotype-phenotype relationship is fundamental in biology. With the benefit from next-generation sequencing and high-throughput phenotyping methodologies, there have been generated much genome and phenome data for Saccharomyces cerevisi...

Machine-learned analysis of the association of next-generation sequencing-based genotypes with persistent pain after breast cancer surgery.

Pain
Cancer and its surgical treatment are among the most important triggering events for persistent pain, but additional factors need to be present for the clinical manifestation, such as variants in pain-relevant genes. In a cohort of 140 women undergoi...

HMMRATAC: a Hidden Markov ModeleR for ATAC-seq.

Nucleic acids research
ATAC-seq has been widely adopted to identify accessible chromatin regions across the genome. However, current data analysis still utilizes approaches initially designed for ChIP-seq or DNase-seq, without considering the transposase digested DNA fragm...

Compositional data network analysis via lasso penalized D-trace loss.

Bioinformatics (Oxford, England)
MOTIVATION: With the development of high-throughput sequencing techniques for 16S-rRNA gene profiling, the analysis of microbial communities is becoming more and more attractive and reliable. Inferring the direct interaction network among microbial c...

Analysis of machine learning algorithms as integrative tools for validation of next generation sequencing data.

European review for medical and pharmacological sciences
OBJECTIVE: While next generation sequencing (NGS) has become the technology of choice for clinical diagnostics, most genetic laboratories still use Sanger sequencing for orthogonal confirmation of NGS results. Previous studies have shown that when th...