ArticleBMC genomics2015
Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer.
Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 29 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.
- Salivary metabolites for pancreatic cancer diagnosis: a systematic review and meta-analysis.BMC gastroenterology · 2025Pooled it
- A review on multi-omics integration for aiding study design of large scale TCGA cancer datasets.BMC genomics · 2025Review
- Comprehensive applications of the artificial intelligence technology in new drug research and development.Health information science and systems · 2024Review
- miRNAs in pancreatic cancer progression and metastasis.Clinical & experimental metastasis · 2024Review
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- Systems Biology in Cancer Diagnosis Integrating Omics Technologies and Artificial Intelligence to Support Physician Decision Making.Journal of personalized medicine · 2023Review
- Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges.Frontiers in pharmacology · 2023Review
- Clustering analysis revealed the autophagy classification and potential autophagy regulators' sensitivity of pancreatic cancer based on multi-omics data.Cancer medicine · 2023Article
- The Impact of Biomarkers in Pancreatic Ductal Adenocarcinoma on Diagnosis, Surveillance and Therapy.Cancers · 2022Review
- Gene Expression Characteristics of Tumor and Adjacent Non-Tumor Tissues of Pancreatic Ductal Adenocarcinoma (PDAC) In-Silico.Iranian journal of biotechnology · 2022Article
- Integrated multi-omics analysis of ovarian cancer using variational autoencoders.Scientific reports · 2021Article
- Article
- NMFNA: A Non-negative Matrix Factorization Network Analysis Method for Identifying Modules and Characteristic Genes of Pancreatic Cancer.Frontiers in genetics · 2021Article
- Prediction of survival and recurrence in patients with pancreatic cancer by integrating multi-omics data.Scientific reports · 2020Article
- Article
- Artificial Intelligence (AI)-Based Systems Biology Approaches in Multi-Omics Data Analysis of Cancer.Frontiers in oncology · 2020Review
- Computational Oncology in the Multi-Omics Era: State of the Art.Frontiers in oncology · 2020Review
- FABP4 and MMP9 levels identified as predictive factors for poor prognosis in patients with nonalcoholic fatty liver using data mining approaches and gene expression analysis.Scientific reports · 2019Article
- A proposed protocol based on integrative metabonomics analysis for the rapid detection and mechanistic understanding of sulfur fumigation of Chinese herbal medicines.RSC advances · 2019Article
- Discovery of the Oncogenic Parp1, a Target of bcr-abl and a Potential Therapeutic, in mir-181a/PPFIA1 Signaling Pathway.Molecular therapy. Nucleic acids · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundmicroRNA (miRNA) expression plays an influential role in cancer classification and malignancy, and miRNAs are feasible as alternative diagnostic markers for pancreatic cancer, a highly aggressive neoplasm with silent early symptoms, high metastatic potential, and resistance to conventional therapies.
methodsIn this study, we evaluated the benefits of multi-omics data analysis by integrating miRNA and mRNA expression data in pancreatic cancer. Using support vector machine (SVM) modelling and leave-one-out cross validation (LOOCV), we evaluated the diagnostic performance of single- or multi-markers based on miRNA and mRNA expression profiles from 104 PDAC tissues and 17 benign pancreatic tissues. For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) data depository. For validation, miRNA activity was estimated by miRNA-target gene interaction and mRNA expression datasets in pancreatic cancer.
resultsUsing a comprehensive identification approach, we successfully identified 705 multi-markers having powerful diagnostic performance for PDAC. In addition, these marker candidates annotated with cancer pathways using gene ontology analysis.
conclusionsOur prediction models have strong potential for the diagnosis of pancreatic cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.