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

Identification of candidate miRNA biomarkers for pancreatic ductal adenocarcinoma by weighted gene co-expression network analysis

15 Feb 2017

Abstract excerpt

PURPOSE: Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy with a dismal prognosis which is, among others, due to a lack of suitable biomarkers and therapeutic targets. Previously, basic gene expression analysis methods have been used for their identification, but recently new algorithms have been developed allowing more comprehensive data analyses. Among them, weighted gene co-expression...

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 MicroRNA in disease regulation
Share to Pancreatic and Hepatic Oncology Research

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 28205147
DOI: 10.1007/s13402-017-0315-y

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 4 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identification of candidate miRNA biomarkers for pancreatic ductal adenocarcinoma by weighted gene co-expression network analysisPMID 28205147Read ↗

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

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

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

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

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

Integrated Analysis of Multi-Omics Data to Identify Prognostic Genes for Pancreatic Cancer.Semantic proximity Read ↗

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

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

Identification of early diagnosis markers of pancreatic ductal adenocarcinoma (PDAC) using publicly available transcriptomic tumor and blood sample dataSemantic proximity Read ↗

Integrated analysis of multi-omics data to identification of prognostic genes for pancreatic cancerSemantic proximity Read ↗

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