DocumentCode :
3035689
Title :
Gene classification and regulatory prediction based on transcriptional modeling
Author :
Tagkopoulos, Ilias ; Serpanos, Dimitrios
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ
fYear :
2005
fDate :
21-21 Dec. 2005
Firstpage :
29
Lastpage :
34
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 protein-protein 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
Keywords :
DNA; genetic engineering; medical image processing; molecular biophysics; pattern classification; pattern clustering; proteins; biclustering algorithm; calculated p-values; gene classification; multistate partition functions; precision-recall curves; protein-DNA interactions; protein-protein interactions; thermodynamic models; transcriptional modeling; Clustering algorithms; DNA; Gene expression; Logic; Partitioning algorithms; Performance analysis; Predictive models; Protein engineering; Sequences; Thermodynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Information Technology, 2005. Proceedings of the Fifth IEEE International Symposium on
Conference_Location :
Athens
Print_ISBN :
0-7803-9313-9
Type :
conf
DOI :
10.1109/ISSPIT.2005.1577065
Filename :
1577065
Link To Document :
بازگشت