ArticleJournal of biosciences2007
Analysis of breast cancer progression using principal component analysis and clustering.
Article in Journal of biosciences, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 44 citations in OpenAlex.
- Machine Learning Empowered a Graphical User Interface on Native Fluorescence to Predict Breast Cancer.ACS omega · 2025Article
- Identification of MAEA protein as a potential target for chemoresistance in osteosarcoma using bioinformatics and proteomic analysis.Frontiers in oncology · 2025Article
- Autoencoder-based multimodal prediction of non-small cell lung cancer survival.Scientific reports · 2023Article
- Patient subgrouping with distinct survival rates via integration of multiomics data on a Grassmann manifold.BMC medical informatics and decision making · 2022Article
- AI applications in functional genomics.Computational and structural biotechnology journal · 2021Review
- Review
- Deep learning-based ovarian cancer subtypes identification using multi-omics data.BioData mining · 2020Article
- Dysregulated lncRNA-miRNA-mRNA Network Reveals Patient Survival-Associated Modules and RNA Binding Proteins in Invasive Breast Carcinoma.Frontiers in genetics · 2019Article
- Deep Learning-Based Multi-Omics Data Integration Reveals Two Prognostic Subtypes in High-Risk Neuroblastoma.Frontiers in genetics · 2018Article
- HER2/ErbB2-induced breast cancer cell migration and invasion require p120 catenin activation of Rac1 and Cdc42.The Journal of biological chemistry · 2010Article
- Presence of an in situ component is associated with reduced biological aggressiveness of size-matched invasive breast cancer.British journal of cancer · 2010Article
- Transforming growth factor-beta signaling: emerging stem cell target in metastatic breast cancer?Breast cancer research and treatment · 2009Review
- Changes in serum and exudate creatine phosphokinase concentrations as an indicator of deep tissue injury: a pilot study.International wound journal · 2008Article
Corrections and comments
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Authors and funding
5 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We develop a new technique to analyse microarray data which uses a combination of principal components analysis and consensus ensemble k-clustering to find robust clusters and gene markers in the data. We apply our method to a public microarray breast cancer dataset which has expression levels of genes in normal samples as well as in three pathological stages of disease; namely, atypical ductal hyperplasia or ADH, ductal carcinoma in situ or DCIS and invasive ductal carcinoma or IDC. Our method averages over clustering techniques and data perturbation to find stable, robust clusters and gene markers. We identify the clusters and their pathways with distinct subtypes of breast cancer (Luminal,Basal and Her2+). We confirm that the cancer phenotype develops early (in early hyperplasia or ADH stage) and find from our analysis that each subtype progresses from ADH to DCIS to IDC along its own specific pathway, as if each was a distinct disease.
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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 OpenQuestion graph.