Article

Unsupervised machine learning identifies distinct molecular and phenotypic ALS subtypes in post-mortem motor cortex and blood expression data

2023-04-25

Abstract excerpt

<h4>ABSTRACT</h4> <h4>Background</h4> Amyotrophic lateral sclerosis (ALS) displays considerable clinical, genetic and molecular heterogeneity. Machine learning approaches have shown potential to disentangle complex disease landscapes and they have been utilised for patient stratification in ALS. However, lack of independent validation in different populations and in pre-mortem tissue samples have greatly limited t...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 4a58f823-e212-5899-bcb3-4427257e079f
DOI: 10.1101/2023.04.21.23288942

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Unsupervised machine learning identifies distinct molecular and phenotypic ALS subtypes in post-mortem motor cortex and blood expression dataDOI 10.1101/2023.04.21.23288942Read

Machine learning evaluation of gene expression-based ALS subtypes across brain and blood tissuesSemantic proximity Read

Unsupervised machine-learning identifies clinically distinct subtypes of ALS that reflect different genetic architectures and biological mechanismsSemantic proximity Read

Classification of ALS Molecular Subtypes: A Review of Machine Learning Applications and Their Clinical ValueSemantic proximity Read

ALS molecular subtypes are a combination of cellular, genetic, and pathological features learned by deep multiomics classifiersSemantic proximity Read

RNA sequencing of peripheral blood in amyotrophic lateral sclerosis reveals distinct molecular subtypes: Considerations for biomarker discoverySemantic proximity Read

Transcriptomics Analyses of ALS Post-mortem Motor Cortex highlight alteration and potential biomarkers in the Neuropeptide Signalling pathwaySemantic proximity Read

ALS blood expression profiling identifies new biomarkers, patient subgroups, and evidence for neutrophilia and hypoxia.Semantic proximity Read

Identification and prediction of ALS subgroups using machine learningSemantic proximity Read

Molecular Taxonomy of Sporadic Amyotrophic Lateral Sclerosis Using Disease-Associated GenesSemantic proximity Read

Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker studySemantic proximity Read

Advances in the genetic classification of amyotrophic lateral sclerosis.Semantic proximity Read

Machine learning analysis reveals biomarkers for the detection of neurodegenerative diseasesSemantic proximity Read