Correlation between Gene Expression and GO Semantic Similarity
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Agent based intelligent search framework for product information using ontology mapping
Journal of Intelligent Information Systems
Ontology Mapping Between Heterogeneous Product Taxonomies in an Electronic Commerce Environment
International Journal of Electronic Commerce
Data-Fusion in Clustering Microarray Data: Balancing Discovery and Interpretability
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Ontology - supported machine learning and decision support in biomedicine
DILS'07 Proceedings of the 4th international conference on Data integration in the life sciences
Attempt to design a bio-medical knowledge discovery system
International Journal of Bio-Inspired Computation
Using Gene Ontology to enhance effectiveness of similarity measures for microarray data
International Journal of Data Mining and Bioinformatics
Incorporating biological domain knowledge into cluster validity assessment
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
An information theoretic approach to assessing gene-ontology-driven similarity and its application
International Journal of Data Mining and Bioinformatics
| Hi-index | 0.00 |
This research explores the feasibility of semanticsimilarity approaches to supporting predictive tasks infunctional genomics. It aims to establish potentialrelationships between ontology-based similarity ofgene products and important functional properties,such as gene expression correlation. Similaritymeasures based on the information content of the GeneOntology (GO) were analyzed. Models have beenimplemented using data obtained from well-knownstudies in S. cerevisiae. Results suggest that there mayexist significant relationships between gene expressioncorrelation and semantic similarity. Analyses ofprotein complex data show that, in general, there is asignificant correlation between the semantic similarityexhibited by a pair of genes and the probability offinding them in the same complex. These results canalso be interpreted as an assessment of the quality andconsistency of the information represented in the GO.