Systems Metabolic Engineering Meets Machine Learning: A New Era for Data‐Driven Metabolic Engineering

The recent increase in high‐throughput capacity of ‘omics datasets combined with advances and interest in machine learning (ML) have created great opportunities for systems metabolic engineering. In this regard, data‐driven modeling methods have become increasingly valuable to metabolic strain desig...

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Veröffentlicht in:	Biotechnology journal 2019-09, Vol.14 (9), p.e1800416-n/a
Hauptverfasser:	Presnell, Kristin V., Alper, Hal S.
Format:	Artikel
Sprache:	eng
Schlagworte:	Biotechnology - methods Machine Learning metabolic engineering Metabolic Engineering - methods omics strain Systems Biology - methods systems modeling
Online-Zugang:	Volltext
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