Cluster-based characterization of gene over-expression in Cancer sets

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Mining techniques are needed to extract important information from huge high dimensional gene expression sets. Targeting unique expression behavior as over/under-expression is specific to gene expression data and is needed to explore another direction in the relation of genes to tumor conditions. This research proposes criteria for filtering over-expression genes, identifying over-expression related samples and using them to characterize over-expression behaviour in gene clusters and outliers. In return, hypothetical marker genes and functional relations can be provided, ready for approval by the aid of other datasets/results. Experiments are performed on breast cancer expression data.

Original languageEnglish
Title of host publicationProceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10
Pages74-79
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10 - Cairo, Egypt
Duration: 29 Nov 20101 Dec 2010

Other

Other2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10
CountryEgypt
CityCairo
Period29/11/101/12/10

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Keywords

  • Clustering
  • Gene expression
  • Outliers
  • Over-expression

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Hardware and Architecture

Cite this

Yousri, N. (2010). Cluster-based characterization of gene over-expression in Cancer sets. In Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10 (pp. 74-79). [5687289] https://doi.org/10.1109/ISDA.2010.5687289