ArticlePloS one2024
Lung cancer clustering by identification of similarities and discrepancies of DNA copy numbers using maximal information coefficient.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Statistical Methods for Detecting Nonlinear Relationships in Gene Expression and Omics Data: A Review.International journal of molecular sciences · 2026Review
- Frequency Ranking of Imaging Biomarkers for Lung Cancer Risk Stratification Using a Hybrid Elastic Net Method.Cancers · 2026Article
- Article
- Habitat-based radiomics from contrast-enhanced CT and clinical data to predict lymph node metastasis in clinical N0 peripheral lung adenocarcinoma ≤ 3 cm.Scientific reports · 2025Article
- A Holistic Approach to Implementing Artificial Intelligence in Lung Cancer.Indian journal of surgical oncology · 2025Review
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Authors and funding
4 authors.
Funding
Abstract
Lung cancer is the second most diagnosed cancer and the first cause of cancer related death for men and women in the United States. Early detection is essential as patient survival is not optimal and recurrence rate is high. Copy number (CN) changes in cancer populations have been broadly investigated to identify CN gains and deletions associated with the cancer. In this research, the similarities between cancer and paired peripheral blood samples are identified using maximal information coefficient (MIC) and the spatial locations with substantially high MIC scores in each chromosome are used for clustering analysis. The results showed that a sizable reduction of feature set can be obtained using only a subset of locations with high MIC values. The clustering performance was evaluated using both true rate and normalized mutual information (NMI). Clustering results using the reduced feature set outperformed the performance of clustering using entire feature set in several chromosomes that are highly associated with lung cancer with several identified oncogenes.
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