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Discovering pathway cross-talks based on functional relations between pathways
BACKGROUND: In 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 p...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521217/ https://www.ncbi.nlm.nih.gov/pubmed/23282018 http://dx.doi.org/10.1186/1471-2164-13-S7-S25 |
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author | Hsu, Chia-Lang Yang, Ueng-Cheng |
author_facet | Hsu, Chia-Lang Yang, Ueng-Cheng |
author_sort | Hsu, Chia-Lang |
collection | PubMed |
description | BACKGROUND: In 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. RESULTS: This 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. CONCLUSIONS: This function-based approach appears to be more sensitive and able to infer more biologically significant and explainable pathway relations. |
format | Online Article Text |
id | pubmed-3521217 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35212172012-12-14 Discovering pathway cross-talks based on functional relations between pathways Hsu, Chia-Lang Yang, Ueng-Cheng BMC Genomics Proceedings BACKGROUND: In 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. RESULTS: This 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. CONCLUSIONS: This function-based approach appears to be more sensitive and able to infer more biologically significant and explainable pathway relations. BioMed Central 2012-12-07 /pmc/articles/PMC3521217/ /pubmed/23282018 http://dx.doi.org/10.1186/1471-2164-13-S7-S25 Text en Copyright ©2012 Hsu et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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. |
spellingShingle | Proceedings Hsu, Chia-Lang Yang, Ueng-Cheng Discovering pathway cross-talks based on functional relations between pathways |
title | Discovering pathway cross-talks based on functional relations between pathways |
title_full | Discovering pathway cross-talks based on functional relations between pathways |
title_fullStr | Discovering pathway cross-talks based on functional relations between pathways |
title_full_unstemmed | Discovering pathway cross-talks based on functional relations between pathways |
title_short | Discovering pathway cross-talks based on functional relations between pathways |
title_sort | discovering pathway cross-talks based on functional relations between pathways |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3521217/ https://www.ncbi.nlm.nih.gov/pubmed/23282018 http://dx.doi.org/10.1186/1471-2164-13-S7-S25 |
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