Machine Learning and Big Data-enabled Biotechnology
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Machine Learning and Big Data-enabled Biotechnology

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Beschreibung

<p><b>Enables researchers and engineers to gain insights into the capabilities of machine learning approaches to power applications in their fields</b></p><p><i>Machine Learning and Big Data-enabled Biotechnology</i> discusses how machine learning and big data can be used in biotechnology for a wide breadth of topics, providing tools essential to support efforts in process control, reactor performance evaluation, and research target identification.</p><p>Topics explored in <i>Machine Learning and Big Data-enabled Biotechnology</i> include:</p><ul><li>Deep learning approaches for synthetic biology part design and automated approaches for GSM development from DNA sequences</li> <li>De novo protein structure and design tools, pathway discovery and retrobiosynthesis, enzyme functional classifications, and proteomics machine learning approaches</li> <li>Metabolomics big data approaches, metabolic production, strain engineering, flux design, and use of generative AI and natural language processing for cell models</li> <li>Automated function and learning in biofoundries and strain designs</li> <li>Machine learning predictions of phenotype and bioreactor performance</li></ul> <p><i>Machine Learning and Big Data-enabled Biotechnology</i> earns a well-deserved spot on the bookshelves of reaction, process, catalytic, and environmental engineers seeking to explore the vast opportunities presented by rapidly developing technologies.</p>

Artikeldetails

EAN
9783527354740
Sprache
Englisch
Einband / Art
Buch
Maße
247 x 174 x 28 mm
Erscheinungsjahr
2026
Verlag / Hersteller
Wiley-VCH GmbH

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Machine Learning and Big Data-enabled Biotechnology

130,95 €