Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy.

BMC bioinformatics - 21 Jun 2018

Crowgey Erin L, Marsh Adam G, Robinson Karyn G, Yeager Stephanie K, Akins Robert E

Abstract excerpt

BACKGROUND: Spastic cerebral palsy (CP) is a leading cause of physical disability. Most people with spastic CP are born with it, but early diagnosis is challenging, and no current biomarker platform readily identifies affected individuals. The aim of this study was to evaluate epigenetic profiles as biomarkers for spastic CP. A novel analysis pipeline was employed to assess DNA methylation patterns between...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biomarkers
Share to Cerebral Palsy
Share to DNA Methylation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Epigenomics

Share to Genome, Human

Share to Machine Learning

Share to Pattern Recognition, Automated

Share to Sequence Analysis, DNA

Source

Open in PubMed Open full text

Identifiers

PMID: 29925314
DOI: 10.1186/s12859-018-2224-0
PMCID: PMC6011336

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy.PMID 29925314Read ↗

Deep Learning/Artificial Intelligence and Blood-Based DNA Epigenomic Prediction of Cerebral PalsySemantic proximity Read ↗

Whole‑genome scale identification of methylation markers specific for cerebral palsy in monozygotic discordant twins.Semantic proximity Read ↗

Epigenome-wide analysis in newborn blood spots from monozygotic twins discordant for cerebral palsy reveals consistent regional differences in DNA methylationSemantic proximity Read ↗

Chronological age prediction based on DNA methylation: Massive parallel sequencing and random forest regression.Semantic proximity Read ↗

DNA methylation profile is a quantitative measure of biological aging in childrenSemantic proximity Read ↗

Exome-wide association study identified genetic variants contributing to the risk of cerebral palsySemantic proximity Read ↗

Identification of a candidate enhancer for DMRT3 involved in spastic cerebral palsy pathogenesis.Semantic proximity Read ↗

Devising reliable and accurate epigenetic predictors: choosing the optimal computational solutionSemantic proximity Read ↗

Longitudinal prediction of DNA methylation to forecast epigenetic outcomesSemantic proximity Read ↗

Morphology‐based molecular classification of spinal cord ependymomas using deep neural networksSemantic proximity Read ↗

The association between DNA methylation and human height and a prospective model of DNA methylation-based height prediction.Semantic proximity Read ↗

Study of global DNA methylation in monozygotic twins with cerebral palsy.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.