Gene expression analysis with integrated fuzzy C-means and pathway analysis

Mingrui Zhang, Beya Adamu, Chi Cheng Lin, Ping Yang

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

2 Scopus citations

Abstract

A workflow for associating fuzzy clusters to biological pathways has been implemented as a Java-based software tool. Its software implementation is comprised of a correlation-based fuzzy c-means algorithm and an enrichment test on Kyoto Encyclopedia of Genes and Genomes' pathways. We applied this workflow to gene expression in classification of lung cancer cell types and achieved satisfactory results. The software could aid in the validation of results of fuzzy clustering algorithms and the exploration of un-annotated associations between genes and gene ontology categories.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages936-939
Number of pages4
DOIs
StatePublished - 2011
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: Aug 30 2011Sep 3 2011

Other

Other33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
CountryUnited States
CityBoston, MA
Period8/30/119/3/11

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

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  • Cite this

    Zhang, M., Adamu, B., Lin, C. C., & Yang, P. (2011). Gene expression analysis with integrated fuzzy C-means and pathway analysis. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 936-939). [6090211] https://doi.org/10.1109/IEMBS.2011.6090211