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

Weighted gene co-expression network analysis reveals key genes involved in pancreatic ductal adenocarcinoma development

30 May 2016

Abstract excerpt

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Up till now, the patient's prognosis remains poor which, among others, is due to the paucity of reliable early diagnostic biomarkers. In the past, candidate diagnostic biomarkers and therapeutic targets have been delineated from genes that were found to be differentially expressed in normal versus tumour samples. Recently, new...

Read the complete abstract on PubMed

Topics

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

Share to Ferroptosis and cancer prognosis
Share to GDF15 and Related Biomarkers
Share to Pancreatic and Hepatic Oncology Research

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 27240826
DOI: 10.1007/s13402-016-0283-7

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Weighted gene co-expression network analysis reveals key genes involved in pancreatic ductal adenocarcinoma developmentPMID 27240826Read ↗

Identification of candidate miRNA biomarkers for pancreatic ductal adenocarcinoma by weighted gene co-expression network analysisSemantic proximity Read ↗

Co-expression analysis of pancreatic cancer proteome reveals biology and prognostic biomarkersSemantic proximity Read ↗

Candidate Genes Identified by Constructing a Weighted Gene Co-Expression Network and Key Prognostic Factors of Pancreatic AdenocarcinomaSemantic proximity Read ↗

Identification of Survival-Associated Hub Genes in Pancreatic Adenocarcinoma Based on WGCNASemantic proximity Read ↗

Gene Expression Network Analysis of Precursor Lesions in Familial Pancreatic CancerSemantic proximity Read ↗

Identification of a stemness-related prognostic model in Pancreatic ductal adenocarcinoma by Weighted gene co-expression network analysisSemantic proximity Read ↗

Analysis of Immune-Related Signatures Related to CD4+ T Cell Infiltration With Gene Co-Expression Network in Pancreatic AdenocarcinomaSemantic proximity Read ↗

Identification of diagnostic biomarkers via weighted correlation network analysis in colorectal cancer using a system biology approachSemantic proximity Read ↗

Development of a four-gene prognostic model for pancreatic cancer based on transcriptome dysregulationSemantic proximity Read ↗

Weighted gene co-expression network analysis identifies potential candidate biomarkers for adenocarcinoma of the esophagogastric junctionSemantic proximity Read ↗

Multidimensional analyses identify genes of high priority for pancreatic cancer researchSemantic proximity Read ↗

Bioinformatic Analysis Suggests That Three Hub Genes May Be a Vital Prognostic Biomarker in Pancreatic Ductal AdenocarcinomaSemantic proximity Read ↗

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