High-dimensional Pattern Discovery
High-Dimensional Pattern Discovery is a methodological framework within high-dimensional data analysis that enables the identification and interpretation of latent structural regularities in data characterized by a large number of interrelated variables.
55
Publications
2.2K
Citations
204
Authors
107
Institutions
Publications per year
2017–2026
14
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Analyzing microarray data using quantitative association rules
Elisabeth Georgii, Lothar Richter, Ulrich Rückert et al. · Bioinformatics · 2005 · 102 citations
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Stanford University
Stanford, United States
3 h-index
10 publications
392 citations
Hunter Medical Research Institute
Newcastle, Australia
2 h-index
4 publications
54 citations

University of Vermont
Burlington, United States
2 h-index
2 publications
29 citations

The University of Melbourne
Melbourne, Australia
2 h-index
4 publications
298 citations
University of California, Berkeley
Berkeley, United States
2 h-index
3 publications
178 citations
City University of New York
New York, United States
2 h-index
2 publications
106 citations
University of Newcastle Australia
Newcastle, Australia
2 h-index
4 publications
54 citations
Academy of Mathematics and Systems Science
Beijing, China
2 h-index
2 publications
73 citations
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Repository · 3 publications · 97 citations
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2 publications · 183 citations
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TKDE · 2 publications · 71 citations
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Repository · 2 publications · 47 citations
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2 publications · 70 citations
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