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

Integrated Transcriptomics-Proteomics Analysis Identifies Molecular Phenotypic Alterations Associated with Colorectal Cancer.

Journal of proteome research - 5 Jan 2024

Liu Jingjing, Jin Xinghua, Qiu Chengchao, Han Ping, Wang Yixuan, Zhao Jian, Wu Jing, Yan Neng, Song Xiaofeng

Abstract excerpt

Understanding the pathogenesis and finding diagnostic markers for colorectal cancer (CRC) are the key to its diagnosis and treatment. Integrated transcriptomics and proteomics analysis can be used to characterize alterations of molecular phenotypes and reveal the hidden pathogenesis of CRC. This study employed a novel strategy integrating transcriptomics and proteomics to identify pathological molecular pathways...

Read the complete abstract on PubMed

Topics

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

Share to Biomarkers, Tumor
Share to Colorectal Neoplasms

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Gene Expression Profiling

Share to Gene Expression Regulation, Neoplastic

Share to Phenotype

Share to Proteomics

Share to Reproducibility of Results

Source

Identifiers

PMID: 37909265
DOI: 10.1021/acs.jproteome.3c00526

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

Integrated Transcriptomics-Proteomics Analysis Identifies Molecular Phenotypic Alterations Associated with Colorectal Cancer.PMID 37909265Read ↗

Identification of Key Candidate Genes and Pathways in Colorectal Cancer by Integrated Bioinformatical Analysis.Semantic proximity Read ↗

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

Integrating proteomics and transcriptomics for the identification of potential targets in early colorectal cancerSemantic proximity Read ↗

The Role of Proteomics and Genomics in the Development of Colorectal Cancer Diagnostic Tools and Potential New TreatmentsSemantic proximity Read ↗

An integrative transcriptome analysis reveals potential predictive, prognostic biomarkers and therapeutic targets in colorectal cancerSemantic proximity Read ↗

Pathway analysis of genome-wide association study and transcriptome data highlights new biological pathways in colorectal cancer.Semantic proximity Read ↗

Identification of key genes in colorectal cancer diagnosis by weighted gene co-expression network analysisSemantic proximity Read ↗

The identification of a common different gene expression signature in patients with colorectal cancerSemantic proximity Read ↗

Integrative Gene Expression Profiling Analysis to Investigate Potential Prognostic Biomarkers for Colorectal CancerSemantic proximity Read ↗

Identification of key genes involved in the development and progression of early‑onset colorectal cancer by co‑expression network analysisSemantic proximity Read ↗

Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysisSemantic proximity Read ↗

Construction of CeRNA Regulatory Network based on WGCNA Reveals Diagnosis Biomarkers for Colorectal CancerSemantic proximity Read ↗

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