Fuzzy clustering in drug design: Application to cocaine abuse

Amit Banerjee; Carol A. Venanzi; Milind Misra; Rajesh N. Davé

doi:10.1109/nafips.2004.1336297

Fuzzy clustering in drug design: Application to cocaine abuse

Amit Banerjee, Carol A. Venanzi, Milind Misra, Rajesh N. Davé

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

This paper describes a fuzzy clustering methodology for selecting representative clusters for conformational analysis. A novel feature extraction procedure based on the structural properties of the molecule is presented. A composite feature vector is developed and the practical applicability of two fuzzy relational clustering techniques, NERF c-means and FRC, is demonstrated. Several cluster validity measures are applied and are shown to provide reliable information about the validity of the partitions produced by the clustering techniques.

Original language	English (US)
Pages	308-313
Number of pages	6
DOIs	https://doi.org/10.1109/nafips.2004.1336297
State	Published - 2004
Event	NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies - Banff, Alta, Canada Duration: Jun 27 2004 → Jun 30 2004

Other

Other	NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies
Country/Territory	Canada
City	Banff, Alta
Period	6/27/04 → 6/30/04

All Science Journal Classification (ASJC) codes

General Computer Science
General Mathematics

Keywords

Cocaine
Feature extraction
Fuzzy relational clustering
Molecular conformations

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10.1109/nafips.2004.1336297

Cite this

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title = "Fuzzy clustering in drug design: Application to cocaine abuse",

abstract = "This paper describes a fuzzy clustering methodology for selecting representative clusters for conformational analysis. A novel feature extraction procedure based on the structural properties of the molecule is presented. A composite feature vector is developed and the practical applicability of two fuzzy relational clustering techniques, NERF c-means and FRC, is demonstrated. Several cluster validity measures are applied and are shown to provide reliable information about the validity of the partitions produced by the clustering techniques.",

keywords = "Cocaine, Feature extraction, Fuzzy relational clustering, Molecular conformations",

author = "Amit Banerjee and Venanzi, {Carol A.} and Milind Misra and Dav{\'e}, {Rajesh N.}",

year = "2004",

doi = "10.1109/nafips.2004.1336297",

language = "English (US)",

pages = "308--313",

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Banerjee, A, Venanzi, CA, Misra, M & Davé, RN 2004, 'Fuzzy clustering in drug design: Application to cocaine abuse', Paper presented at NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies, Banff, Alta, Canada, 6/27/04 - 6/30/04 pp. 308-313. https://doi.org/10.1109/nafips.2004.1336297

Fuzzy clustering in drug design: Application to cocaine abuse. / Banerjee, Amit; Venanzi, Carol A.; Misra, Milind et al.
2004. 308-313 Paper presented at NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies, Banff, Alta, Canada.

Research output: Contribution to conference › Paper › peer-review

TY - CONF

T1 - Fuzzy clustering in drug design

T2 - NAFIPS 2004 - Annual Meeting of the North American Fuzzy Information Processing Society: Fuzzy Sets in the Heart of the Canadian Rockies

AU - Banerjee, Amit

AU - Venanzi, Carol A.

AU - Misra, Milind

AU - Davé, Rajesh N.

PY - 2004

Y1 - 2004

N2 - This paper describes a fuzzy clustering methodology for selecting representative clusters for conformational analysis. A novel feature extraction procedure based on the structural properties of the molecule is presented. A composite feature vector is developed and the practical applicability of two fuzzy relational clustering techniques, NERF c-means and FRC, is demonstrated. Several cluster validity measures are applied and are shown to provide reliable information about the validity of the partitions produced by the clustering techniques.

AB - This paper describes a fuzzy clustering methodology for selecting representative clusters for conformational analysis. A novel feature extraction procedure based on the structural properties of the molecule is presented. A composite feature vector is developed and the practical applicability of two fuzzy relational clustering techniques, NERF c-means and FRC, is demonstrated. Several cluster validity measures are applied and are shown to provide reliable information about the validity of the partitions produced by the clustering techniques.

KW - Cocaine

KW - Feature extraction

KW - Fuzzy relational clustering

KW - Molecular conformations

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Y2 - 27 June 2004 through 30 June 2004

ER -

Fuzzy clustering in drug design: Application to cocaine abuse

Abstract

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All Science Journal Classification (ASJC) codes

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