Discovering pathway cross-talks based on functional relations between pathways

BMC Genomics

Proceedings

Ueng-Cheng Yang¹  Chia-Lang Hsu² 

[1] Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan;Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei, Taiwan;Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan;Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei, Taiwan;Department of Life Science, National Taiwan University, Taipei, Taiwan;

关键词: Gene Ontology;    False Positive Rate;    Pathway Interaction;    Shared Component;    Pathway Interaction Database;   

DOI  :  10.1186/1471-2164-13-S7-S25

来源: Springer

【 摘 要 】

BackgroundIn biological systems, pathways coordinate or interact with one another to achieve a complex biological process. Studying how they influence each other is essential for understanding the intricacies of a biological system. However, current methods rely on statistical tests to determine pathway relations, and may lose numerous biologically significant relations.ResultsThis study proposes a method that identifies the pathway relations by measuring the functional relations between pathways based on the Gene Ontology (GO) annotations. This approach identified 4,661 pathway relations among 166 pathways from Pathway Interaction Database (PID). Using 143 pathway interactions from PID as testing data, the function-based approach (FBA) is able to identify 93% of pathway interactions, better than the existing methods based on the shared components and protein-protein interactions. Many well-known pathway cross-talks are only identified by FBA. In addition, the false positive rate of FBA is significantly lower than others via pathway co-expression analysis.ConclusionsThis function-based approach appears to be more sensitive and able to infer more biologically significant and explainable pathway relations.

【 授权许可】

Unknown   
© Hsu et al.; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.