Using fuzzy memberships to core patterns to interpret connectedness in gene expression clusters

Noha Yousri, M. S. Kamel, M. A. Ismail

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

3 Citations (Scopus)

Abstract

Connectivity based clustering can reveal the continuity of gene expression patterns, and thus can discover interrelations between tumor types, as well as regulatory relations between genes that can lead to discovering gene pathways. Pattern cores are a subset of expression patterns that are representatives of the whole set of patterns and can be used to reveal the structure of the data as well as that of the clusters, especially in the presence of huge data sets. This work presents a fuzzy approach that starts by finding the density-based expression pattern cores. Those cores are then clustered into core clusters and fuzzy memberships to those cores are calculated for all patterns in the data set. The whole data set is then clustered into pattern clusters using a connectivity-based algorithm, where a pattern cluster might contain one or more core clusters. The fuzzy memberships to core clusters in each pattern cluster are used to interpret the connectedness of the pattern cluster using the structure of core clusters, as well as to identify how each pattern is related to one or more tumor types.

Original languageEnglish
Title of host publicationProceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW
Pages115-122
Number of pages8
DOIs
Publication statusPublished - 1 Dec 2007
Externally publishedYes
Event2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW - San Jose, CA, United States
Duration: 2 Nov 20074 Nov 2007

Other

Other2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW
CountryUnited States
CitySan Jose, CA
Period2/11/074/11/07

Fingerprint

Gene expression
Tumors
Genes

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Yousri, N., Kamel, M. S., & Ismail, M. A. (2007). Using fuzzy memberships to core patterns to interpret connectedness in gene expression clusters. In Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW (pp. 115-122). [4425409] https://doi.org/10.1109/BIBMW.2007.4425409

Using fuzzy memberships to core patterns to interpret connectedness in gene expression clusters. / Yousri, Noha; Kamel, M. S.; Ismail, M. A.

Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW. 2007. p. 115-122 4425409.

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

Yousri, N, Kamel, MS & Ismail, MA 2007, Using fuzzy memberships to core patterns to interpret connectedness in gene expression clusters. in Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW., 4425409, pp. 115-122, 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW, San Jose, CA, United States, 2/11/07. https://doi.org/10.1109/BIBMW.2007.4425409
Yousri N, Kamel MS, Ismail MA. Using fuzzy memberships to core patterns to interpret connectedness in gene expression clusters. In Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW. 2007. p. 115-122. 4425409 https://doi.org/10.1109/BIBMW.2007.4425409
Yousri, Noha ; Kamel, M. S. ; Ismail, M. A. / Using fuzzy memberships to core patterns to interpret connectedness in gene expression clusters. Proceedings - 2007 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW. 2007. pp. 115-122
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