A novel clustering approach: Global optimum search with enhanced positioning

Meng P. Tan, James R. Broach, Christodoulos A. Floudas

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Cluster analysis of DNA expression data is a useful tool for identifying biologically relevant gene groupings. It is hence important to apply a rigorous yet intuitive clustering algorithm to uncover these genomic relationships. Here, we describe a clustering framework [1,2] based on a variant of the Generalized Benders Decomposition, the Global Optimum Search [3,4]. We apply the proposed algorithm to experimental DNA microarray data and compare the results to that obtained with some commonly-used algorithms. We also propose an extension to iteratively uncover the optimal biologically coherent structures.

Original languageEnglish (US)
Title of host publication17th European Symposium on Computer Aided Process Engineering
EditorsValentin Plesu, Paul Serban Agachi
Pages983-988
Number of pages6
DOIs
StatePublished - Dec 1 2007

Publication series

NameComputer Aided Chemical Engineering
Volume24
ISSN (Print)1570-7946

All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Computer Science Applications

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    P. Tan, M., R. Broach, J., & A. Floudas, C. (2007). A novel clustering approach: Global optimum search with enhanced positioning. In V. Plesu, & P. S. Agachi (Eds.), 17th European Symposium on Computer Aided Process Engineering (pp. 983-988). (Computer Aided Chemical Engineering; Vol. 24). https://doi.org/10.1016/S1570-7946(07)80188-X