Treffer: Algorithmic and complexity issues of three clustering methods in microarray data analysis
Title:
Algorithmic and complexity issues of three clustering methods in microarray data analysis
Authors:
Source:
COCOON 2005 : computing and combinatorics (Kunming, 16-29 August 2005)Lecture notes in computer science. :74-83
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 24 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Recherche operationnelle. Gestion, Operational research. Management science, Recherche opérationnelle et modèles formalisés de gestion, Operational research and scientific management, Flots dans les réseaux. Problèmes combinatoires, Flows in networks. Combinatorial problems, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Recherche information. Graphe, Information retrieval. Graph, Analyse amas, Cluster analysis, Analisis cluster, Bioinformatique, Bioinformatics, Bioinformática, Classification, Clasificación, Complexité algorithme, Algorithm complexity, Complejidad algoritmo, Modélisation, Modeling, Modelización, Méthode polynomiale, Polynomial method, Método polinomial, Problème NP difficile, NP hard problem, Problema NP duro, Problème combinatoire, Combinatorial problem, Problema combinatorio, Puce à DNA, DNA chip, Pulga de DNA, Temps polynomial, Polynomial time, Tiempo polinomial
Document Type:
Konferenz
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Mathematics National University of Singapore, Singapore 117543, Singapore
The Inst. of High Performance Computing, Singapore 117528, Singapore
The Inst. of High Performance Computing, Singapore 117528, Singapore
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Operational research. Management
Operational research. Management
Accession Number:
edscal.17096311
Database:
PASCAL Archive
Weitere Informationen
The complexity, approximation and algorithmic issues of several clustering problems are studied. These non-traditional clustering problems arise from recent studies in microarray data analysis. We prove the following results. (1) Two variants of the Order-Preserving Submatrix problem are NP-hard. There are polynomial-time algorithms for the Order-Preserving Submatrix Problem when the condition or gene sets are given. (2) The Smooth Subset problem cannot be approximable with ratio 0.5 + S for any constant 6 > 0 unless NP=P. (3) Inferring plaid model problem is NP-hard.