ArticleCell cycle (Georgetown, Tex.)2017
Data aggregation at the level of molecular pathways improves stability of experimental transcriptomic and proteomic data.
Article in Cell cycle (Georgetown, Tex.), 2017. 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.
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- NetActivity enhances transcriptional signals by combining gene expression into robust gene set activity scores through interpretable autoencoders.Nucleic acids research · 2024Article
- Number of human protein interactions correlates with structural, but not regulatory conservation of the respective genes.Frontiers in genetics · 2024Article
- Pan-cancer experimental characteristic of human transcriptional patterns connected with telomerase reverse transcriptase (Frontiers in genetics · 2024Article
- Algorithmically Reconstructed Molecular Pathways as the New Generation of Prognostic Molecular Biomarkers in Human Solid Cancers.Proteomes · 2023Article
- Depiction of neuroendocrine features associated with immunotherapy response using a novel one-class predictor in lung adenocarcinoma.Discover oncology · 2023Article
- Uniformly shaped harmonization combines human transcriptomic data from different platforms while retaining their biological properties and differential gene expression patterns.Frontiers in molecular biosciences · 2023Article
- Next-Generation Grade and Survival Expression Biomarkers of Human Gliomas Based on Algorithmically Reconstructed Molecular Pathways.International journal of molecular sciences · 2022Article
- Better Agreement of Human Transcriptomic and Proteomic Cancer Expression Data at the Molecular Pathway Activation Level.International journal of molecular sciences · 2022Article
- Transcriptomic Portraits and Molecular Pathway Activation Features of Adult Spinal Intramedullary Astrocytomas.Frontiers in oncology · 2022Article
- Gene Expression-Based Signature Can Predict Sorafenib Response in Kidney Cancer.Frontiers in molecular biosciences · 2022Article
- Pathway Enrichment Analysis of Microarray Data.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Human blood serum can donor-specifically antagonize effects of EGFR-targeted drugs on squamous carcinoma cell growth.Heliyon · 2021Article
- Article
- Algorithmic Annotation of Functional Roles for Components of 3,044 Human Molecular Pathways.Frontiers in genetics · 2021Article
- System, Method and Software for Calculation of a Cannabis Drug Efficiency Index for the Reduction of Inflammation.International journal of molecular sciences · 2020Article
- RNA Sequencing in Comparison to Immunohistochemistry for Measuring Cancer Biomarkers in Breast Cancer and Lung Cancer Specimens.Biomedicines · 2020Article
- RNA sequencing profiles and diagnostic signatures linked with response to ramucirumab in gastric cancer.Cold Spring Harbor molecular case studies · 2020Article
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21 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High throughput technologies opened a new era in biomedicine by enabling massive analysis of gene expression at both RNA and protein levels. Unfortunately, expression data obtained in different experiments are often poorly compatible, even for the same biologic samples. Here, using experimental and bioinformatic investigation of major experimental platforms, we show that aggregation of gene expression data at the level of molecular pathways helps to diminish cross- and intra-platform bias otherwise clearly seen at the level of individual genes. We created a mathematical model of cumulative suppression of data variation that predicts the ideal parameters and the optimal size of a molecular pathway. We compared the abilities to aggregate experimental molecular data for the 5 alternative methods, also evaluated by their capacity to retain meaningful features of biologic samples. The bioinformatic method OncoFinder showed optimal performance in both tests and should be very useful for future cross-platform data analyses.
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