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

Key Modules and Hub Genes Identified by Coexpression Network Analysis for Revealing Novel Biomarkers for Spina Bifida

2 Dec 2020

Abstract excerpt

Spina bifida is a common neural tube defect (NTD) accounting for 5-10% of perinatal mortalities. As a polygenic disease, spina bifida is caused by a combination of genetic and environmental factors, for which the precise molecular pathogenesis is still not systemically understood. In the present study, we aimed to identify the related gene module that might play a vital role in the occurrence and development of...

Read the complete abstract on PubMed

Topics

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

Share to Fetal and Pediatric Neurological Disorders
Share to Folate and B Vitamins Research
Share to Spinal Dysraphism and Malformations

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 33343629
DOI: 10.3389/fgene.2020.583316

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Key Modules and Hub Genes Identified by Coexpression Network Analysis for Revealing Novel Biomarkers for Spina BifidaPMID 33343629Read ↗

Weighted Gene Co-expression Network Analysis of Key Biomarkers Associated With Bronchopulmonary DysplasiaSemantic proximity Read ↗

Weighted gene co-expression network analysis of expression data of monozygotic twins identifies specific modules and hub genes related to BMISemantic proximity Read ↗

Weighted Gene Co-Expression Network Analysis (WGCNA) Discovered Novel Long Non-Coding RNAs for Polycystic Ovary SyndromeSemantic proximity Read ↗

Exploration and Validation of Hub Genes and Pathways in the Progression of Hypoplastic Left Heart Syndrome via Weighted Gene Co-Expression Network AnalysisSemantic proximity Read ↗

Integrative multiomic analysis on single-nucleotide variants identifies candidate genes for human craniofacial malformationSemantic proximity Read ↗

Identification of potential biomarkers in the peripheral blood of neonates with bronchopulmonary dysplasia using WGCNA and machine learning algorithmsSemantic proximity Read ↗

Exploration and validation of hub genes and pathways in the progression of hypoplastic left heart syndrome via weighted gene co-expression network analysis.Semantic proximity Read ↗

Identification of hub‐methylated differentially expressed genes in patients with gestational diabetes mellitus by multi‐omic WGCNA basing epigenome‐wide and transcriptome‐wide profilingSemantic proximity Read ↗

Identification of Key Genes and Pathways Associated with Preeclampsia by a WGCNA and an Evolutionary ApproachSemantic proximity Read ↗

Shared molecular networks in orofacial and neural tube development.Semantic proximity Read ↗

Unearthing of key genes driving the infertility risk of cryptorchidism via weighted gene co- expression networkSemantic proximity Read ↗

Identifying the hub genes for Duchenne muscular dystrophy and Becker muscular dystrophy by weighted correlation network analysisSemantic proximity Read ↗

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