Cited by 2,116Gene expression and cancer classificationAdvanced Clustering Algorithms ResearchBayesian Methods and Mixture Models

The DOI matches its Crossref record; 48 of the 49 references it cites were found in a registry or an index.

Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data

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  1. Cowell, F. A. (1995). Measuring Inequality. New York: Prentice Hall.

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Metadata

Authors
Monti, S., Tamayo, P., Mesirov, J., & Golub, T.
Affiliations
Massachusetts Institute of Technology (US)
Venue
Machine Learning
Published
2003-07
Volume
52
Issue
1-2
Pages
91-118
ISSN
  • 0885-6125 (ISSN-L)
  • 1573-0565
OpenAlex
W1548779692
Cited by
2,116
References
49
Citations by year
2026: 134 · 2025: 113 · 2024: 155 · 2023: 133 · 2022: 139 · 2021: 192 · 2020: 123 · 2019: 112 · 2018: 120 · 2017: 100 · 2016: 85 · 2015: 94 · 2014: 78 · 2013: 77 · 2012: 80
FWCI
8.98
Type
journal article
Language
en
Open access
Locations
Machine Learning (publishedVersion)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
  • Physical Sciences › Computer Science › Artificial Intelligence › Advanced Clustering Algorithms Research
  • Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
Keywords
consensus clustering, gene expression microarrays, cluster validation, cluster stability, resampling, cluster visualization, optimal number of clusters, K-means clustering, self-organizing maps, Bayesian clustering, sensitivity to initial conditions

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