Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Machine Learning and Big Data-Enabled Biotechnology

Machine Learning and Big Data-Enabled Biotechnology

Alper, Hal S.

Hardcover

Series: Advanced Biotechnology

BiologyGeneral Computers

ISBN10: 3527354743
ISBN13: 9783527354740
Publisher: Wiley-Vch
Published: May 11 2026
Pages: 432
Weight: 1.95
Height: 0.94 Width: 6.69 Depth: 9.61
Language: English

Enables researchers and engineers to gain insights into the capabilities of machine learning approaches to power applications in their fields

Machine Learning and Big Data-enabled Biotechnology 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.

Topics explored in Machine Learning and Big Data-enabled Biotechnology include:

  • Deep learning approaches for synthetic biology part design and automated approaches for GSM development from DNA sequences
  • De novo protein structure and design tools, pathway discovery and retrobiosynthesis, enzyme functional classifications, and proteomics machine learning approaches
  • Metabolomics big data approaches, metabolic production, strain engineering, flux design, and use of generative AI and natural language processing for cell models
  • Automated function and learning in biofoundries and strain designs
  • Machine learning predictions of phenotype and bioreactor performance

Machine Learning and Big Data-enabled Biotechnology 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.

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