Unsupervised gene selection and clustering using simulated annealing

Maurizio Filippone; Francesco Masulli; Stefano Rovetta

doi:10.1007/11676935_28

Unsupervised gene selection and clustering using simulated annealing

Maurizio Filippone^*, Francesco Masulli, Stefano Rovetta

^*Corresponding author for this work

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

9 Scopus citations

Abstract

When applied to genomic data, many popular unsupervised explorative data analysis tools based on clustering algorithms often fail due to their small cardinality and high dimensionality. In this paper we propose a wrapper method for gene selection based on simulated annealing and unsupervised clustering. The proposed approach, even if computationally intensive, permits to select the most relevant features (genes), and to rank their relevance, allowing to improve the results of clustering algorithms.

Original language	English (US)
Title of host publication	Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers
Pages	229-235
Number of pages	7
DOIs	https://doi.org/10.1007/11676935_28
State	Published - 2006
Event	6th International Workshop - Fuzzy Logic and Applications - Crema, Italy Duration: Sep 15 2005 → Sep 17 2005

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3849 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th International Workshop - Fuzzy Logic and Applications
Country/Territory	Italy
City	Crema
Period	09/15/05 → 09/17/05

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

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10.1007/11676935_28

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Filippone, M., Masulli, F., & Rovetta, S. (2006). Unsupervised gene selection and clustering using simulated annealing. In Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers (pp. 229-235). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3849 LNAI). https://doi.org/10.1007/11676935_28

Filippone, Maurizio ; Masulli, Francesco ; Rovetta, Stefano. / Unsupervised gene selection and clustering using simulated annealing. Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers. 2006. pp. 229-235 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Unsupervised gene selection and clustering using simulated annealing",

abstract = "When applied to genomic data, many popular unsupervised explorative data analysis tools based on clustering algorithms often fail due to their small cardinality and high dimensionality. In this paper we propose a wrapper method for gene selection based on simulated annealing and unsupervised clustering. The proposed approach, even if computationally intensive, permits to select the most relevant features (genes), and to rank their relevance, allowing to improve the results of clustering algorithms.",

author = "Maurizio Filippone and Francesco Masulli and Stefano Rovetta",

year = "2006",

doi = "10.1007/11676935_28",

language = "English (US)",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Filippone, M, Masulli, F & Rovetta, S 2006, Unsupervised gene selection and clustering using simulated annealing. in Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3849 LNAI, pp. 229-235, 6th International Workshop - Fuzzy Logic and Applications, Crema, Italy, 09/15/05. https://doi.org/10.1007/11676935_28

Unsupervised gene selection and clustering using simulated annealing. / Filippone, Maurizio; Masulli, Francesco; Rovetta, Stefano.
Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers. 2006. p. 229-235 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3849 LNAI).

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

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AU - Masulli, Francesco

AU - Rovetta, Stefano

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N2 - When applied to genomic data, many popular unsupervised explorative data analysis tools based on clustering algorithms often fail due to their small cardinality and high dimensionality. In this paper we propose a wrapper method for gene selection based on simulated annealing and unsupervised clustering. The proposed approach, even if computationally intensive, permits to select the most relevant features (genes), and to rank their relevance, allowing to improve the results of clustering algorithms.

AB - When applied to genomic data, many popular unsupervised explorative data analysis tools based on clustering algorithms often fail due to their small cardinality and high dimensionality. In this paper we propose a wrapper method for gene selection based on simulated annealing and unsupervised clustering. The proposed approach, even if computationally intensive, permits to select the most relevant features (genes), and to rank their relevance, allowing to improve the results of clustering algorithms.

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Filippone M, Masulli F, Rovetta S. Unsupervised gene selection and clustering using simulated annealing. In Fuzzy Logic and Applications - 6th International Workshop, WILF 2005, Revised Selected Papers. 2006. p. 229-235. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11676935_28

Unsupervised gene selection and clustering using simulated annealing

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