Evaluating pathway enumeration algorithms in metabolic engineering case studies
The design of cell factories for the production of compounds involves the search for suitable heterologous pathways. Different strategies have been proposed to infer such pathways, but most are optimization approaches with specific objective functions, not suited to enumerate multiple pathways. In t...
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| Other Authors: | , , |
| Format: | conferencePaper |
| Language: | eng |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1822/33017 |
| Country: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/33017 |
| Summary: | The design of cell factories for the production of compounds involves the search for suitable heterologous pathways. Different strategies have been proposed to infer such pathways, but most are optimization approaches with specific objective functions, not suited to enumerate multiple pathways. In this work, we analyze two pathway enumeration algorithms based on graph representations: the Solution Structure Generation and the Find Path algorithms. Both are capable of enumerating exhaustively multiple pathways using network topology. We study their capabilities and limitations when designing novel heterologous pathways, by applying these methods on two case studies of synthetic metabolic engineering related to the production of butanol and vanillin. |
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