Efficient Reconstruction of Predictive Consensus Metabolic Network Models.
Understanding cellular function requires accurate, comprehensive representations of metabolism. Genome-scale, constraint-based metabolic models (GSMs) provide such representations, but their usability is often hampered by inconsistencies at various levels, in particular for concurrent models. COMMGE...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2016-08-01
|
| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1005085 |
| _version_ | 1818735034008338432 |
|---|---|
| author | Ruben G A van Heck Mathias Ganter Vitor A P Martins Dos Santos Joerg Stelling |
| author_facet | Ruben G A van Heck Mathias Ganter Vitor A P Martins Dos Santos Joerg Stelling |
| author_sort | Ruben G A van Heck |
| collection | DOAJ |
| description | Understanding cellular function requires accurate, comprehensive representations of metabolism. Genome-scale, constraint-based metabolic models (GSMs) provide such representations, but their usability is often hampered by inconsistencies at various levels, in particular for concurrent models. COMMGEN, our tool for COnsensus Metabolic Model GENeration, automatically identifies inconsistencies between concurrent models and semi-automatically resolves them, thereby contributing to consolidate knowledge of metabolic function. Tests of COMMGEN for four organisms showed that automatically generated consensus models were predictive and that they substantially increased coherence of knowledge representation. COMMGEN ought to be particularly useful for complex scenarios in which manual curation does not scale, such as for eukaryotic organisms, microbial communities, and host-pathogen interactions. |
| first_indexed | 2024-12-18T00:14:50Z |
| format | Article |
| id | doaj.art-3da064f53d804f92982dfb5521566ccb |
| institution | Directory Open Access Journal |
| issn | 1553-734X 1553-7358 |
| language | English |
| last_indexed | 2024-12-18T00:14:50Z |
| publishDate | 2016-08-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj.art-3da064f53d804f92982dfb5521566ccb2022-12-21T21:27:33ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582016-08-01128e100508510.1371/journal.pcbi.1005085Efficient Reconstruction of Predictive Consensus Metabolic Network Models.Ruben G A van HeckMathias GanterVitor A P Martins Dos SantosJoerg StellingUnderstanding cellular function requires accurate, comprehensive representations of metabolism. Genome-scale, constraint-based metabolic models (GSMs) provide such representations, but their usability is often hampered by inconsistencies at various levels, in particular for concurrent models. COMMGEN, our tool for COnsensus Metabolic Model GENeration, automatically identifies inconsistencies between concurrent models and semi-automatically resolves them, thereby contributing to consolidate knowledge of metabolic function. Tests of COMMGEN for four organisms showed that automatically generated consensus models were predictive and that they substantially increased coherence of knowledge representation. COMMGEN ought to be particularly useful for complex scenarios in which manual curation does not scale, such as for eukaryotic organisms, microbial communities, and host-pathogen interactions.https://doi.org/10.1371/journal.pcbi.1005085 |
| spellingShingle | Ruben G A van Heck Mathias Ganter Vitor A P Martins Dos Santos Joerg Stelling Efficient Reconstruction of Predictive Consensus Metabolic Network Models. PLoS Computational Biology |
| title | Efficient Reconstruction of Predictive Consensus Metabolic Network Models. |
| title_full | Efficient Reconstruction of Predictive Consensus Metabolic Network Models. |
| title_fullStr | Efficient Reconstruction of Predictive Consensus Metabolic Network Models. |
| title_full_unstemmed | Efficient Reconstruction of Predictive Consensus Metabolic Network Models. |
| title_short | Efficient Reconstruction of Predictive Consensus Metabolic Network Models. |
| title_sort | efficient reconstruction of predictive consensus metabolic network models |
| url | https://doi.org/10.1371/journal.pcbi.1005085 |
| work_keys_str_mv | AT rubengavanheck efficientreconstructionofpredictiveconsensusmetabolicnetworkmodels AT mathiasganter efficientreconstructionofpredictiveconsensusmetabolicnetworkmodels AT vitorapmartinsdossantos efficientreconstructionofpredictiveconsensusmetabolicnetworkmodels AT joergstelling efficientreconstructionofpredictiveconsensusmetabolicnetworkmodels |