ArticleInternational journal of molecular sciences2019
Identifying Methylation Pattern and Genes Associated with Breast Cancer Subtypes.
Article in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
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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.
The trial behind it
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Who cites it
28 citing papers in PubMed.
- DeepCMS: A Feature Selection-Driven Model for Cancer Molecular Subtyping with a Case Study on Testicular Germ Cell Tumors.Diagnostics (Basel, Switzerland) · 2025Article
- DNA methylation biomarkers for the diagnosis and treatment management of breast cancer: where are we now?Epigenomics · 2025Review
- Discovery and performance of DNA methylation panels for cancer detection and classification in blood.bioRxiv : the preprint server for biology · 2025Article
- A review of the use of tumour DNA methylation for breast cancer subtyping and prediction of outcomes.Clinical epigenetics · 2025Review
- DNA methylation patterns in breast cancer, paired benign tissue from ipsilateral and contralateral breast, and healthy controls.Breast cancer research : BCR · 2025Article
- DNA methylation in breast cancer: early detection and biomarker discovery through current and emerging approaches.Journal of translational medicine · 2025Review
- Prediction of Solubility of Proteins in Escherichia coli Based on Functional and Structural Features Using Machine Learning Methods.The protein journal · 2024Article
- Epigenetics, Microbiota, and Breast Cancer: A Systematic Review.Life (Basel, Switzerland) · 2024Review
- MyoV: a deep learning-based tool for the automated quantification of muscle fibers.Briefings in bioinformatics · 2024Article
- Identification of Phase-Separation-Protein-Related Function Based on Gene Ontology by Using Machine Learning Methods.Life (Basel, Switzerland) · 2023Article
- Characterization of chromatin accessibility patterns in different mouse cell types using machine learning methods at single-cell resolution.Frontiers in genetics · 2023Article
- Identification of genes related to immune enhancement caused by heterologous ChAdOx1-BNT162b2 vaccines in lymphocytes at single-cell resolution with machine learning methods.Frontiers in immunology · 2023Article
- Value of genomics- and radiomics-based machine learning models in the identification of breast cancer molecular subtypes: a systematic review and meta-analysis.Annals of translational medicine · 2022Article
- Hub genes associated with immune cell infiltration in breast cancer, identified through bioinformatic analyses of multiple datasets.Cancer biology & medicine · 2022Article
- Hypermethylation of TMEM240 predicts poor hormone therapy response and disease progression in breast cancer.Molecular medicine (Cambridge, Mass.) · 2022Article
- The epigenetics of breast cancer - Opportunities for diagnostics, risk stratification and therapy.Epigenetics · 2022Article
- Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method.Life (Basel, Switzerland) · 2022Article
- Berberine as a potential agent for breast cancer therapy.Frontiers in oncology · 2022Review
- Predicting RNA 5-Methylcytosine Sites by Using Essential Sequence Features and Distributions.BioMed research international · 2022Article
- Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method.Frontiers in molecular biosciences · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Breast cancer is regarded worldwide as a severe human disease. Various genetic variations, including hereditary and somatic mutations, contribute to the initiation and progression of this disease. The diagnostic parameters of breast cancer are not limited to the conventional protein content and can include newly discovered genetic variants and even genetic modification patterns such as methylation and microRNA. In addition, breast cancer detection extends to detailed breast cancer stratifications to provide subtype-specific indications for further personalized treatment. One genome-wide expression-methylation quantitative trait loci analysis confirmed that different breast cancer subtypes have various methylation patterns. However, recognizing clinically applied (methylation) biomarkers is difficult due to the large number of differentially methylated genes. In this study, we attempted to re-screen a small group of functional biomarkers for the identification and distinction of different breast cancer subtypes with advanced machine learning methods. The findings may contribute to biomarker identification for different breast cancer subtypes and provide a new perspective for differential pathogenesis in breast cancer subtypes.
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What Socratic 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 Socratic graph.