Portraits of breast cancer progression

Portraits of breast cancer progression

Background: Clustering analysis of microarray data is often criticized for giving ambiguous results because of sensitivity to data perturbation or clustering techniques used. In this paper, we describe a new method based on principal component analysis and ensemble consensus clustering that avoids t...

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Bibliographic Details
Main Authors: Alexe, Gabriela, Scanfeld, Daniel, Tamayo, Pablo, Ganesan, Shridar, DeLisi, Charles, Bhanot, Gyan, Dalgin, Gul S., Mesirov, Jill P.
Other Authors: Broad Institute of MIT and Harvard
Format: Article
Language:English
Published: BioMed Central Ltd 2010
Subjects:
Evaluation studies
Algorithms
Artificial intelligence
Breast neoplasms, diagnosis
Breast neoplasms, metabolism
Carcinoma, ductal, diagnosis
Carcinoma, ductal, metabolism
Diagnosis, computer-assisted methods
Disease progression
Female
Gene expression profiling, methods
Humans
Neoplasm proteins, analysis
Oligonucleotide array sequence analysis, methods
Pattern recognition, automated methods
Principal component analysis
Reproducibility of results
Sensitivity and specificity
Neoplasm proteins
Tumor markers, biological, analysis
Online Access:http://hdl.handle.net/1721.1/59307

Internet

http://hdl.handle.net/1721.1/59307

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