Article

Probabilistic modeling methods for cell-free DNA methylation based cancer classification

2021-06-18

Abstract excerpt

<h4>Background</h4> cfMeDIP-seq is a low-cost method for determining the DNA methylation status of cell-free DNA and it has been successfully combined with statistical methods for accurate cancer diagnostics. We investigate the diagnostic classification aspect by applying statistical tests and dimension reduction techniques for feature selection and probabilistic modeling for the cancer type classification, and w...

Topics

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

Identifiers and source

Literature Corpus work: 3f274533-cd61-522e-82e0-4108b0377e2c
DOI: 10.1101/2021.06.18.444402

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Probabilistic modeling methods for cell-free DNA methylation based cancer classificationDOI 10.1101/2021.06.18.444402Read

Νovel methylation biomarkers in liquid biopsy and classifying biosignatures for the clinical management of Breast CancerSemantic proximity Read

Prediction model for malignant pulmonary nodules based on cfMeDIP‐seq and machine learningSemantic proximity Read

CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNASemantic proximity Read

A Bayesian Nonparametric Approach to Discover Clinico-Genetic Associations across Cancer TypesSemantic proximity Read

Artificial Intelligence in cancer epigenomics: a review on advances in pan-cancer detection and precision medicineSemantic proximity Read

Machine Classification of Methylomes in CancerSemantic proximity Read

ATAC-seq Guided Interpretable Machine Learning Reveals Cancer-Specific Chromatin Features in Cell-free DNASemantic proximity Read

MethylBERT:‬ ‭A‬ ‭Transformer-based‬ ‭model‬ ‭for‬ ‭read-level‬ ‭DNA‬ ‭methylation‬ pattern‬ ‭identification‬ ‭and‬ ‭tumour‬ ‭deconvolution‬Semantic proximity Read

A Fast, Affordable, and Minimally Invasive Diagnostic Test for Cancer of Unknown Primary Using DNA Methylation ProfilingSemantic proximity Read

Cost-effective methylome sequencing of cell-free DNA for accurately detecting and locating cancerSemantic proximity Read

cfMIND: A read-level methylation framework for accurate non-invasive disease detection using cell-free DNASemantic proximity Read

Accurate prediction of pan-cancer types using machine learning with minimal number of DNA methylation sitesSemantic proximity Read