Bioinformatics, AI, and Machine Learning in Microbial Drug Development

Name: Bioinformatics, AI, and Machine Learning in Microbial Drug Development
Price: 175 USD
Availability: InStock
ISBN: 9780443330322

by Vagish Dwibedi, Nancy George, Santosh Kumar Rath, Swapnil Kajale

1st Edition

Publisher: Academic Press

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Microbiology

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Book Details

Print ISBN	9780443330322
eText ISBN	9780443330339
Publisher	Academic Press
Publishing Year	2025
Edition	1st Edition
Language	English
Pages	330

Bioinformatics, AI, and Machine Learning in Microbial Drug Development, 1st Edition, outlines a framework for combining microbiology, bioinformatics, artificial intelligence, and machine learning within pharmaceutical microbiology. Tailored for researchers working across biosciences in bioinformatics, computational biology, and systems biology, this book establishes systematic methods for discovering therapeutic compounds from microbial sources.

The content explores microbial diversity alongside techniques for the isolation and cultivation of novel microorganisms. Primary topics cover natural product discovery and characterization, synthetic biology and genetic engineering in bioprospecting, multi-omics data integration, and specialized bioinformatics tools for mining microbial genomes and metabolites.

Structured into 4 parts comprising 19 chapters, the text includes practical guidance and case studies throughout its thematic sections. It provides computational bioscientists with a structured reference for applying data integration methods to microbial natural product research.

Chapter 1: Microbial Diversity and Its Relevance to Drug Discovery
Chapter 2: Isolation and Cultivation of Novel Microorganisms for Drug Prospecting
Chapter 3: Natural Product Discovery and Characterization
Chapter 4: Synthetic Biology and Genetic Engineering in Pharmaceutical Bioprospecting
Chapter 5: Multi-Omics Data Integration for Drug Discovery
Chapter 6: Microbial Biotechnology in the Era of Big Data and AI
Chapter 7: Bioinformatics Tools for Mining Microbial Genomes and Metabolites
Chapter 8: Omics Technologies in Microbial Drug Factories
Chapter 9: Machine Learning Applications in Microbial Fermentation and Drug Discovery
Chapter 10: High-Throughput Screening in Microbial Drug Development
Chapter 11: Fermentation Process Optimization for Pharmaceutical Production
Chapter 12: Leveraging Artificial Intelligence for Drug Development and Drug Discovery
Chapter 13: Metabolic Engineering for Drug Production and Drug Discovery
Chapter 14: Overcoming Challenges in Microbial Drug Factory Scale-Up
Chapter 15: Regulatory and Ethical Considerations in Microbial Drug Production
Chapter 16: Intellectual Property and Patents in Microbial Drug Development
Chapter 17: Overcoming Challenges in Microbial Drug Factory Scale-Up
Chapter 18: Sustainability and Green Practices in Microbial Drug Factories
Chapter 19: Epilogue: Microbes, Technology, and the Future of Drug Discovery