Predicting metabolic fluxes from omics data via machine learning: Moving from knowledge-driven towards data-driven approaches
The accurate prediction of phenotypes in microorganisms is a main challenge for systems biology. Genome-scale models (GEMs) are a widely used mathematical formalism for predicting metabolic fluxes using constraint-based modeling methods such as flux balance analysis (FBA). However, they require prio...
| 出版年: | Computational and Structural Biotechnology Journal |
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| 主要な著者: | , , |
| フォーマット: | 論文 |
| 言語: | 英語 |
| 出版事項: |
Elsevier
2023-01-01
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| 主題: | |
| オンライン･アクセス: | http://www.sciencedirect.com/science/article/pii/S2001037023003586 |