ArticleNucleic acids research2017
COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH).
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 69 papers.
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Who cites it
69 citing papers in PubMed, 111 citations in OpenAlex.
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- Molecules interacting with CasL-Like 2 enhances tumor angiogenesis and progression by activating mTOR/HIF1α/VEGF pathway in kidney renal clear cell carcinoma.Scientific reports · 2025Article
- ALDOC and PGK1 coordinately induce glucose metabolism reprogramming and promote development of colorectal cancer.Molecular medicine (Cambridge, Mass.) · 2025Article
- TROAP promotes esophageal squamous cell carcinoma progression via the PI3K/AKT pathway.Journal of cancer research and clinical oncology · 2025Article
- Crotonylation of MCM6 enhances chemotherapeutics sensitivity of breast cancer via inducing DNA replication stress.Cell proliferation · 2025Article
- Identification of TACSTD2 as novel therapeutic targets for cisplatin-induced acute kidney injury by multi-omics data integration.Human genetics · 2024Article
- High expression of YEATS2 as a predictive factor of poor prognosis in patients with hepatocellular carcinoma.Scientific reports · 2024Article
- PERP May Affect the Prognosis of Lung Adenocarcinoma by Inhibiting Apoptosis.Cancer management and research · 2024Article
- Mir-142-3P regulates MAPK protein family by inhibiting 14-3-3η to enhance bone marrow mesenchymal stem cells osteogenesis.Scientific reports · 2023Article
- Type I collagen and fibromodulin enhance the tenogenic phenotype of hASCs and their potential for tendon regeneration.NPJ Regenerative medicine · 2023Article
- Expression and clinical significance of RBBP4 gene in lower-grade glioma: An integrative analysis.Biochemistry and biophysics reports · 2023Article
- A ribosomal gene panel predicting a novel synthetic lethality in non-BRCAness tumors.Signal transduction and targeted therapy · 2023Article
- METTL13 facilitates cell growth and metastasis in gastric cancer via an eEF1A/HN1L positive feedback circuit.Journal of cell communication and signaling · 2023Article
- HSPA6, a novel prognostic and therapeutic biomarker, associated with Ming classification in gastric cancer.Journal of clinical laboratory analysis · 2023Article
- A gene expression profile-based approach to screen the occurrence and predisposed host characteristics of drug-induced liver injury: a case study ofFrontiers in chemistry · 2023Article
- SMURF2 facilitates ubiquitin-mediated degradation of ID2 to attenuate lung cancer cell proliferation.International journal of biological sciences · 2023Article
- HN1L/AP-2γ/PLK1 signaling drives tumor progression and chemotherapy resistance in esophageal squamous cell carcinoma.Cell death & disease · 2022Article
- A single-cell survey unveils cellular heterogeneity and sensitive responses in mouse cortices induced by oral exposure to triphenyl phosphate.Archives of toxicology · 2022Article
- Approaches in Gene Coexpression Analysis in Eukaryotes.Biology · 2022Review
9 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of high-throughput array and sequencing technologies has produced unprecedented amounts of gene expression data in central public depositories, including the Gene Expression Omnibus (GEO). The immense amount of expression data in GEO provides both vast research opportunities and data analysis challenges. Co-expression analysis of high-dimensional expression data has proven effective for the study of gene functions, and several co-expression databases have been developed. Here, we present a new co-expression database, COEXPEDIA (www.coexpedia.org), which is distinctive from other co-expression databases in three aspects: (i) it contains only co-functional co-expressions that passed a rigorous statistical assessment for functional association, (ii) the co-expressions were inferred from individual studies, each of which was designed to investigate gene functions with respect to a particular biomedical context such as a disease and (iii) the co-expressions are associated with medical subject headings (MeSH) that provide biomedical information for anatomical, disease, and chemical relevance. COEXPEDIA currently contains approximately eight million co-expressions inferred from 384 and 248 GEO series for humans and mice, respectively. We describe how these MeSH-associated co-expressions enable the identification of diseases and drugs previously unknown to be related to a gene or a gene group of interest.
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