ArticleJournal of gastrointestinal oncology2022
Diagnostic genes and immune infiltration analysis of colorectal cancer determined by LASSO and SVM machine learning methods: a bioinformatics analysis.
Article in Journal of gastrointestinal oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- NFKB1 as a key player in Tumor biology: from mechanisms to therapeutic implications.Cell biology and toxicology · 2025Pooled it
- Identification of Cellular Senescence-Related Hub Genes in Rheumatoid Arthritis from Bioinformatics Analysis Through Machine Learning up to Verifications in Mouse Macrophages and Tests in Patients.International journal of molecular sciences · 2026Article
- SCRIB is a Shared Transcriptomic Biomarker Candidate Linking Cardioembolic Stroke and Alzheimer's Disease.Journal of molecular neuroscience : MN · 2026Article
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- Machine learning-driven multi-targeted drug discovery in colon cancer using biomarker signatures.NPJ precision oncology · 2025Article
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- Integrating machine learning and bioinformatics approaches for identifying novel diagnostic gene biomarkers in colorectal cancer.Scientific reports · 2024Article
- Identification of novel diagnostic biomarkers associated with liver metastasis in colon adenocarcinoma by machine learning.Discover oncology · 2024Article
- Combining single-cell and bulk RNA sequencing, NK cell marker genes reveal a prognostic and immune status in pancreatic ductal adenocarcinoma.Scientific reports · 2024Article
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- ALOX5AP suppresses osteosarcoma progression via Wnt/β-catenin/EMT pathway and associates with clinical prognosis and immune infiltration.Journal of orthopaedic surgery and research · 2023Article
- Identification of immune-related genes in diagnosing atherosclerosis with rheumatoid arthritis through bioinformatics analysis and machine learning.Frontiers in immunology · 2023Article
- TRIB3, as a robust prognostic biomarker for HNSC, is associated with poor immune infiltration and cancer cell immune evasion.Frontiers in immunology · 2023Article
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Genetic factors account for approximately 35% of colorectal cancer risk. The specificity and sensitivity of previous diagnostic biomarkers for colorectal cancer could not meet the need of clinical application. The expanding scale and inherent complexity of biological data have encouraged a growing use of machine learning to build informative and predictive models of the underlying biological processes. The aim of this study is to identify diagnostic genes of colorectal cancer by using machine learning methods. Methods: The GSE41328 and GSE106582 data sets were downloaded from the Gene Expression Omnibus (GEO) database. The gene expression differences between colon cancer and normal tissues were analyzed. The key colorectal cancer genes were screened and validated by Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine (SVM) regression. Immune cell infiltration and the correlation with the key genes in patients with colon cancer were further analyzed by CIBERSORT. Results: Eleven key genes were identified as biomarkers for colon cancer, namely Conclusions:
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