Gene classification and regulatory prediction based on transcriptional modeling

Ilias Tagkopoulos, Dimitrios Serpanos

Research output: Contribution to conferencePaper

Abstract

We present a methodology that aims to elucidate regulatory mechanisms by grouping together genes which share the same regulatory network. In our method, we use multi-state partition functions and thermodynamic models to derive six distinct correlation classes that correspond to various ProteinProtein and Protein-DNA interactions. We then introduce a novel biclustering algorithm that clusters together genes whose expression profiles exhibit the derived correlations in various conditions. The functional enrichment and statistical significance of the resulting clusters is evaluated by precision-recall curves and calculated p-values. Moreover, we analyzed the upstream regions of all genes that comprise each cluster, in order to verify that the derived correlation classes capture the expression of genes with common regulation. We have been able to identify over hundred strongly conserved sequences, among which eight match well-known regulatory motifs. Finally, further analysis of the identified conserved sequences provides not only an explanation of the classification performance, but serves also as an indicator of the regulatory coherence of various groups.

Original languageEnglish
Pages29-34
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2005
Event5th IEEE International Symposium on Signal Processing and Information Technology - Athens, Greece
Duration: 18 Dec 200521 Dec 2005

Other

Other5th IEEE International Symposium on Signal Processing and Information Technology
CountryGreece
CityAthens
Period18/12/0521/12/05

ASJC Scopus subject areas

  • Engineering(all)

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    Tagkopoulos, I., & Serpanos, D. (2005). Gene classification and regulatory prediction based on transcriptional modeling. 29-34. Paper presented at 5th IEEE International Symposium on Signal Processing and Information Technology, Athens, Greece. https://doi.org/10.1109/ISSPIT.2005.1577065