Extracting global structure from gene expression profiles

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Extracting global structure from gene expression profiles. / Fowlkes, C; Shan, Q; Belongie, S; Malik, J.

METHODS OF MICROARRAY DATA ANALYSIS II. ed. / SM Lin; KF Johnson. Kluwer Academic Publishers Group, 2002. p. 81-90.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Fowlkes, C, Shan, Q, Belongie, S & Malik, J 2002, Extracting global structure from gene expression profiles. in SM Lin & KF Johnson (eds), METHODS OF MICROARRAY DATA ANALYSIS II. Kluwer Academic Publishers Group, pp. 81-90, 2nd Critical Assessment of Microarray Data Analysis (CAMDA 01), DURHAM, New Caledonia, 15/10/2001. https://doi.org/10.1007/0-306-47598-7_6

APA

Fowlkes, C., Shan, Q., Belongie, S., & Malik, J. (2002). Extracting global structure from gene expression profiles. In SM. Lin, & KF. Johnson (Eds.), METHODS OF MICROARRAY DATA ANALYSIS II (pp. 81-90). Kluwer Academic Publishers Group. https://doi.org/10.1007/0-306-47598-7_6

Vancouver

Fowlkes C, Shan Q, Belongie S, Malik J. Extracting global structure from gene expression profiles. In Lin SM, Johnson KF, editors, METHODS OF MICROARRAY DATA ANALYSIS II. Kluwer Academic Publishers Group. 2002. p. 81-90 https://doi.org/10.1007/0-306-47598-7_6

Author

Fowlkes, C ; Shan, Q ; Belongie, S ; Malik, J. / Extracting global structure from gene expression profiles. METHODS OF MICROARRAY DATA ANALYSIS II. editor / SM Lin ; KF Johnson. Kluwer Academic Publishers Group, 2002. pp. 81-90

Bibtex

@inproceedings{21477353255e4af3b1d9d9ba4c6f10db,
title = "Extracting global structure from gene expression profiles",
abstract = "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.",
keywords = "gene expression profiles, clustering analysis, spectral partitioning, IMAGE SEGMENTATION, NORMALIZED CUTS, PATTERNS",
author = "C Fowlkes and Q Shan and S Belongie and J Malik",
year = "2002",
doi = "10.1007/0-306-47598-7_6",
language = "English",
isbn = "1-4020-7111-6",
pages = "81--90",
editor = "SM Lin and KF Johnson",
booktitle = "METHODS OF MICROARRAY DATA ANALYSIS II",
publisher = "Kluwer Academic Publishers Group",
note = "2nd Critical Assessment of Microarray Data Analysis (CAMDA 01) ; Conference date: 15-10-2001 Through 16-10-2001",

}

RIS

TY - GEN

T1 - Extracting global structure from gene expression profiles

AU - Fowlkes, C

AU - Shan, Q

AU - Belongie, S

AU - Malik, J

PY - 2002

Y1 - 2002

N2 - 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.

AB - 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.

KW - gene expression profiles

KW - clustering analysis

KW - spectral partitioning

KW - IMAGE SEGMENTATION

KW - NORMALIZED CUTS

KW - PATTERNS

U2 - 10.1007/0-306-47598-7_6

DO - 10.1007/0-306-47598-7_6

M3 - Article in proceedings

SN - 1-4020-7111-6

SP - 81

EP - 90

BT - METHODS OF MICROARRAY DATA ANALYSIS II

A2 - Lin, SM

A2 - Johnson, KF

PB - Kluwer Academic Publishers Group

T2 - 2nd Critical Assessment of Microarray Data Analysis (CAMDA 01)

Y2 - 15 October 2001 through 16 October 2001

ER -

ID: 302160853