Relational analysis of CpG islands methylation and gene expression in human lymphomas using possibilistic C-means clustering and modified cluster fuzzy density

Ozy Sjahputera, James M. Keller, J. Wade Davis, Kristen H. Taylor, Farahnaz Rahmatpanah, Huidong Shi, Derek T. Anderson, Samuel N. Blisard, Robert H. Luke, Mihail Popescu, Gerald C. Arthur, Charles W. Caldwell

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Heterogeneous genetic and epigenetic alterations are commonly found in human non-Hodgkin's lymphomas (NHL). One such epigenetic alteration is aberrant methylation of gene promoter-related CpG islands, where hypermethylation frequently results in transcriptional inactivation of target genes, while a decrease or loss of promoter methylation (hypomethylation) is frequently associated with transcriptional activation. Discovering genes with these relationships in NHL or other types of cancers could lead to a better understanding of the pathobiology of these diseases. The simultaneous analysis of promoter methylation using Differential Methylation Hybridization (DMH) and its associated gene expression using Expressed CpG Island Sequence Tag (ECIST) microarrays generates a large volume of methylation-expression relational data. To analyze this data, we propose a set of algorithms based on fuzzy sets theory, in particular Possibilistic c-Means (PCM) and cluster fuzzy density. For each gene, these algorithms calculate measures of confidence of various methylation-expression relationships in each NHL subclass. Thus, these tools can be used as a means of high volume data exploration to better guide biological confirmation using independent molecular biology methods.

Original languageEnglish (US)
Pages (from-to)176-188
Number of pages13
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume4
Issue number2
DOIs
StatePublished - Apr 1 2007

Fingerprint

CpG Islands
Methylation
Non-Hodgkin's Lymphoma
Gene expression
Gene Expression
Cluster Analysis
Lymphoma
Promoter
Clustering
Gene
Genes
Epigenomics
Molecular Biology
Fuzzy Set Theory
Microarray
Confidence
Activation
Cancer
Molecular biology
Fuzzy set theory

Keywords

  • Cluster density
  • Clustering
  • Expression
  • Fuzzy sets
  • Methylation
  • Microarray

ASJC Scopus subject areas

  • Biotechnology
  • Genetics
  • Applied Mathematics

Cite this

Relational analysis of CpG islands methylation and gene expression in human lymphomas using possibilistic C-means clustering and modified cluster fuzzy density. / Sjahputera, Ozy; Keller, James M.; Davis, J. Wade; Taylor, Kristen H.; Rahmatpanah, Farahnaz; Shi, Huidong; Anderson, Derek T.; Blisard, Samuel N.; Luke, Robert H.; Popescu, Mihail; Arthur, Gerald C.; Caldwell, Charles W.

In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, Vol. 4, No. 2, 01.04.2007, p. 176-188.

Research output: Contribution to journalArticle

Sjahputera, Ozy ; Keller, James M. ; Davis, J. Wade ; Taylor, Kristen H. ; Rahmatpanah, Farahnaz ; Shi, Huidong ; Anderson, Derek T. ; Blisard, Samuel N. ; Luke, Robert H. ; Popescu, Mihail ; Arthur, Gerald C. ; Caldwell, Charles W. / Relational analysis of CpG islands methylation and gene expression in human lymphomas using possibilistic C-means clustering and modified cluster fuzzy density. In: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2007 ; Vol. 4, No. 2. pp. 176-188.
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