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The recent increase in high-throughput capacity of 'omics datasets combined with advances and interest in machine learning have created great opportunities for systems metabolic engineering. In this regard, data-driven modeling methods have become increasingly valuable to metabolic strain design. In this review we discuss the nature of 'omics and provide a broad introduction to the machine learning algorithms combining these datasets into predictive models of metabolism and metabolic rewiring. Next, we highlight recent work in the literature that utilize such data-driven methods to inform various metabolic engineering efforts for different classes of application including product maximization, understanding and profiling phenotypes, de novo metabolic pathway design, and creation of robust system-scale models for biotechnology. Overall, this review aims to highlight the potential and promise of using machine learning algorithms with metabolic engineering and systems biology related datasets. This article is protected by copyright. All rights reserved.
This article was published in the following journal.
Name: Biotechnology journal
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A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of unlabeled paired input-output training (sample) data.
A MACHINE LEARNING paradigm used to make predictions about future instances based on a given set of labeled paired input-output training (sample) data.
A type of ARTIFICIAL INTELLIGENCE that enable COMPUTERS to independently initiate and execute LEARNING when exposed to new data.
SUPERVISED MACHINE LEARNING algorithm which learns to assign labels to objects from a set of training examples. Examples are learning to recognize fraudulent credit card activity by examining hundreds or thousands of fraudulent and non-fraudulent credit card activity, or learning to make disease diagnosis or prognosis based on automatic classification of microarray gene expression profiles drawn from hundreds or thousands of samples.
Methods and techniques used to modify or select cells and develop conditions for growing cells for biosynthetic production of molecules (METABOLIC ENGINEERING), for generation of tissue structures and organs in vitro (TISSUE ENGINEERING), or for other BIOENGINEERING research objectives.
Bioscience - any of the sciences that deal with living organisms. The study of the nature, behavior, and uses of living organisms as applied to biology. Any of the branches of natural science dealing with living things, such as their structure, b...