Extracting global structure from gene expression profiles
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
We have developed a program, GENECUT, for analyzing datasets from gene expression profiling. GENECUT is based on a pairwise clustering method known as Normalized Cul [Shi and Malik, 1997]. GENECUT extracts global structures by progressively partitioning datasets into well-balanced groups, performing an intuitive k-way partitioning at each stage in contrast to commonly used 2-way partitioning schemes. By making use of the Nystrom approximation, it is possible to perform clustering on very large genomic datasets.
Original language | English |
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Title of host publication | METHODS OF MICROARRAY DATA ANALYSIS II |
Editors | SM Lin, KF Johnson |
Number of pages | 10 |
Publisher | Kluwer Academic Publishers Group |
Publication date | 2002 |
Pages | 81-90 |
ISBN (Print) | 1-4020-7111-6 |
DOIs | |
Publication status | Published - 2002 |
Externally published | Yes |
Event | 2nd Critical Assessment of Microarray Data Analysis (CAMDA 01) - DURHAM, New Caledonia Duration: 15 Oct 2001 → 16 Oct 2001 |
Conference
Conference | 2nd Critical Assessment of Microarray Data Analysis (CAMDA 01) |
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Land | New Caledonia |
By | DURHAM |
Periode | 15/10/2001 → 16/10/2001 |
- gene expression profiles, clustering analysis, spectral partitioning, IMAGE SEGMENTATION, NORMALIZED CUTS, PATTERNS
Research areas
ID: 302160853