ArticleGenes2020
A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.
Article in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of deep learning in cancer epigenetics through DNA methylation analysis.Briefings in bioinformatics · 2023Pooled it
- Identification of exosomal miRNA-based predictive signatures for gestational diabetes mellitus via multi-algorithm machine learning.BMC pregnancy and childbirth · 2026Article
- DNA methylation and machine learning: challenges and perspective toward enhanced clinical diagnostics.Clinical epigenetics · 2025Review
- Deep Learning-Based DNA Methylation Detection in Cervical Cancer Using the One-Hot Character Representation Technique.Diagnostics (Basel, Switzerland) · 2025Article
- UNet with Attention Networks: A Novel Deep Learning Approach for DNA Methylation Prediction in HeLa Cells.Genes · 2025Article
- Subtypes detection of papillary thyroid cancer from methylation assay via Deep Neural Network.Computational and structural biotechnology journal · 2025Article
- Methods in DNA methylation array dataset analysis: A review.Computational and structural biotechnology journal · 2024Review
- Advancing epigenetic profiling in cervical cancer: machine learning techniques for classifying DNA methylation patterns.3 Biotech · 2024Article
- Cancer genetics and deep learning applications for diagnosis, prognosis, and categorization.Journal of biological methods · 2024Review
- Deep-Learning Algorithm and Concomitant Biomarker Identification for NSCLC Prediction Using Multi-Omics Data Integration.Biomolecules · 2022Article
- A Deep Survival EWAS approach estimating risk profile based on pre-diagnostic DNA methylation: An application to breast cancer time to diagnosis.PLoS computational biology · 2022Article
- Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies.Discover oncology · 2022Article
- Identifying predictive signalling networks for Vedolizumab response in ulcerative colitis.International journal of colorectal disease · 2022Article
- Comparison of five supervised feature selection algorithms leading to top features and gene signatures from multi-omics data in cancer.BMC bioinformatics · 2022Article
- Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer.International journal of molecular sciences · 2022Article
- Knowledge structure and emerging trends in the application of deep learning in genetics research: A bibliometric analysis [2000-2021].Frontiers in genetics · 2022Article
- A Deep Learning-Based Framework for Supporting Clinical Diagnosis of Glioblastoma Subtypes.Frontiers in genetics · 2022Article
- Chitosan Nanoparticles Inactivate Alfalfa Mosaic Virus Replication and Boost Innate Immunity inPlants (Basel, Switzerland) · 2021Article
- Computational learning of features for automated colonic polyp classification.Scientific reports · 2021Article
- Identifying anti-TNF response biomarkers in ulcerative colitis using a diffusion-based signalling model.Bioinformatics advances · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
DNA methylation change has been useful for cancer biomarker discovery, classification, and potential treatment development. So far, existing methods use either differentially methylated CpG sites or combined CpG sites, namely differentially methylated regions, that can be mapped to genes. However, such methylation signal mapping has limitations. To address these limitations, in this study, we introduced a combinatorial framework using linear regression, differential expression, deep learning method for accurate biological interpretation of DNA methylation through integrating DNA methylation data and corresponding TCGA gene expression data. We demonstrated it for uterine cervical cancer. First, we pre-filtered outliers from the data set and then determined the predicted gene expression value from the pre-filtered methylation data through linear regression. We identified differentially expressed genes (DEGs) by Empirical Bayes test using Limma. Then we applied a deep learning method, "
Indexed as
Identifiers
What OpenQuestion holds
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.