ArticleBioMed research international2022
Analysis of Lymphoma-Related Genes with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes Enrichment.
Article in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
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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.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Article
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- ZNF473 as a biomarker and potential therapeutic target in cancer: integrated bioinformatics and experimental evidence with a focus on hepatocellular carcinoma.Frontiers in oncology · 2026Article
- Hub genes and common pathogenic mechanisms between COPD and H. pylori infection.Journal, genetic engineering & biotechnology · 2025Article
- LINCRNA01094 Promotes Renal Interstitial Fibrosis via the Mir-513b-5p/ MELK/Smad3 Axis.Endocrine, metabolic & immune disorders drug targets · 2025Article
- Multimodal prognostic models for bladder urothelial carcinoma: uroplakin III combined with serum and demographic data.Frontiers in oncology · 2025Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lymphoma is a serious malignant tumor that contains more than 70 different types and seriously endangers the body's lymphatic system. The lymphatic system is the regulatory center of the immune system and is important in the immune response to foreign antigens and tumors. Studies showed that multiple genetic variants are associated with lymphoma but determining the pathogenic mechanisms remains a challenge. In the present study, we first applied the Gene Ontology (GO) and KEGG pathway enrichment analyses of lymphoma-associated and lymphoma-nonassociated genes. Next, the Boruta and max-relevance and min-redundancy feature selection methods were performed to filter and rank features. Then, features preselected and ranked using the incremental feature selection method were applied for the decision tree model to identify the best GO terms and KEGG pathways and extract classification rules. Results indicate that our predicted features, such as B-cell activation, negative regulation of protein processing, negative regulation of mast cell cytokine production, and natural killer cell-mediated cytotoxicity, are associated with the biological process of lymphoma, consistent with those of recent publications. This study provides a new perspective for future research on the molecular mechanisms of lymphoma.
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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.