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Predictive Integration of Gene Ontology-Driven Similarity and Functional Interactions
Hong Kong, China December 18-December 22
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.130Sixth IEEE International Conference o ...
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Francisco Azuaje, Haiying Wang, Huiru Zheng, Olivier Bodenreider, Alban Chesneau, "Predictive Integration of Gene Ontology-Driven Similarity and Functional Interactions," Data Mining Workshops, International Conference on, pp. 114-119, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006.
 
 
BibTex
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@article{ 10.1109/ICDMW.2006.130,
author = {Francisco Azuaje and Haiying Wang and Huiru Zheng and Olivier Bodenreider and Alban Chesneau},
title = {Predictive Integration of Gene Ontology-Driven Similarity and Functional Interactions},
journal ={Data Mining Workshops, International Conference on},
volume = {0},
year = {2006},
isbn = {0-7695-2702-7},
pages = {114-119},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.130},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Data Mining Workshops, International Conference on
TI - Predictive Integration of Gene Ontology-Driven Similarity and Functional Interactions
SN - 0-7695-2702-7
SP114
EP119
A1 - Francisco Azuaje,
A1 - Haiying Wang,
A1 - Huiru Zheng,
A1 - Olivier Bodenreider,
A1 - Alban Chesneau,
PY - 2006
KW - null
VL - 0
JA - Data Mining Workshops, International Conference on
ER -
 
Francisco Azuaje, University of Ulster, UK
Haiying Wang, University of Ulster, UK
Huiru Zheng, University of Ulster, UK
Olivier Bodenreider, National Institutes of Health., USA
Alban Chesneau, High-Throughput Protein Technologies Group, France
There is a need to develop methods to automatically incorporate prior knowledge to support the prediction and validation of novel functional associations. One such important source is represented by the Gene Ontology (GO)?? and the many model organism databases of gene products annotated to the GO. We investigated quantitative relationships between the GO-driven similarity of genes and their functional interactions by analyzing different types of associations in Saccharomyces cerevisiae and Caenorhabditis elegans. Interacting genes exhibited significantly higher levels of GO-driven similarity (GOS) in comparison to random pairs of genes used as a surrogate for negative interactions. The Biological Process hierarchy provides more reliable results for co-regulatory and protein-protein interactions. GOS represent a relevant resource to support prediction of functional networks in combination with other resources.
Citation:
Francisco Azuaje, Haiying Wang, Huiru Zheng, Olivier Bodenreider, Alban Chesneau, "Predictive Integration of Gene Ontology-Driven Similarity and Functional Interactions," icdmw, pp.114-119, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006
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