Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models.
Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame....
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2014-10-01
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| Series: | PLoS Computational Biology |
| Online Access: | http://europepmc.org/articles/PMC4199484?pdf=render |