ArticleOncotarget2016
Post-transcriptional knowledge in pathway analysis increases the accuracy of phenotypes classification.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Computational Methods for Pathway and Network Analysis with MicroRNAs.Methods in molecular biology (Clifton, N.J.) · 2026Review
- multiDEGGs: Single or Multiomic Differential Network Analysis for Biomarker Discovery and Feature Engineering for Predictive Modeling.Computational and structural biotechnology journal · 2026Article
- The Novel Immunocompetent Eµ-SOX11CCND1 Mouse Model Phenotypically and Molecularly Resembles Human Mantle Cell Lymphoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025Article
- Regulatory QTLs affecting miRNA-mRNA interactions in cancer: mechanisms, methods, and clinical implications.Frontiers in molecular biosciences · 2025Review
- PACO: a Shiny app for comparing perturbed pathways associated with different phenotypes.Bioinformatics advances · 2025Article
- Measuring cancer driving force of chromosomal aberrations through multi-layer Boolean implication networks.PloS one · 2024Article
- TMBcalc: a computational pipeline for identifying pan-cancer Tumor Mutational Burden gene signatures.Frontiers in genetics · 2024Article
- Expression signature of human endogenous retroviruses in chronic lymphocytic leukemia.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- The Ratio of Key Metabolic Transcripts Is a Predictive Biomarker of Breast Cancer Metastasis to the Lung.Cancer research · 2023Article
- PanomiR: a systems biology framework for analysis of multi-pathway targeting by miRNAs.Briefings in bioinformatics · 2023Article
- RAGE inhibition blunts insulin-induced oncogenic signals in breast cancer.Breast cancer research : BCR · 2023Article
- Exploring the Role of Enhancer-Mediated Transcriptional Regulation in Precision Biology.International journal of molecular sciences · 2023Review
- DEGGs: an R package with shiny app for the identification of differentially expressed gene-gene interactions in high-throughput sequencing data.Bioinformatics (Oxford, England) · 2023Article
- Screening of Precancerous Lesions in Women with Human Papillomavirus (HPV) Infection by Molecular Typing and MicroRNA Analysis.Journal of personalized medicine · 2023Article
- Article
- Small RNA-Seq Transcriptome Profiling of Mesothelial and Mesothelioma Cell Lines Revealed microRNA Dysregulation after Exposure to Asbestos-like Fibers.Biomedicines · 2023Article
- A comprehensive survey of the approaches for pathway analysis using multi-omics data integration.Briefings in bioinformatics · 2022Review
- Transcriptome Analysis of Human Endogenous Retroviruses at Locus-Specific Resolution in Non-Small Cell Lung Cancer.Cancers · 2022Article
- Network analysis of synovial RNA sequencing identifies gene-gene interactions predictive of response in rheumatoid arthritis.Arthritis research & therapy · 2022Article
- Dysregulation of microRNAs and tRNA-derived ncRNAs in mesothelial and mesothelioma cell lines after asbestiform fiber exposure.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
motivationPrediction of phenotypes from high-dimensional data is a crucial task in precision biology and medicine. Many technologies employ genomic biomarkers to characterize phenotypes. However, such elements are not sufficient to explain the underlying biology. To improve this, pathway analysis techniques have been proposed. Nevertheless, such methods have shown lack of accuracy in phenotypes classification.
resultsHere we propose a novel methodology called MITHrIL (Mirna enrIched paTHway Impact anaLysis) for the analysis of signaling pathways, which extends the work of Tarca et al., 2009. MITHrIL augments pathways with missing regulatory elements, such as microRNAs, and their interactions with genes. The method takes as input the expression values of genes and/or microRNAs and returns a list of pathways sorted according to their degree of deregulation, together with the corresponding statistical significance (p-values). Our analysis shows that MITHrIL outperforms its competitors even in the worst case. In addition, our method is able to correctly classify sets of tumor samples drawn from TCGA. AVAILABILITY: MITHrIL is freely available at the following URL: http://alpha.dmi.unict.it/mithril/.
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