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Nowadays, the field of microbiology is undergoing a revolutionary change due to the emergence of Artificial Intelligence (AI). AI is being used to analyze massive data in a predictable form, about the behavior of microorganisms, to solve microbial classification-related problems, exploring the interaction between microorganisms and the surrounding environment. It also helps to extract novel microbial metabolites which have been used in various fields like medical, food and agricultural industries. As the pace of innovation in Microbiology is accelerating, the use of AI in these industries will be beneficial. AI will not only show its extraordinary potential in expanding the market of antibiotics, food, and agriculture but also offer an eco-friendly, safer, and profitable solution to the respective industries. It would be challenging to search out specific features and discuss future research on AI in microbiology with a wide perspective. Uncovering extended functions of AI in Microbiology. Production and development of novel drug targets through AI. Challenges for using and selecting appropriate AI tools in health, agriculture and food sector
This textbook addresses global and local environmental problems and the involvement of microorganisms in their development and remediation. In particular, methodological aspects, some of them molecular genetic, for the study of microbial communities are considered. Overall, the prominent role of microorganisms in various material cycles is presented. In addition to biochemical principles for the degradation of environmental pollutants, the use of microorganisms in environmental biotechnological processes for the purification of air, water or soil as well as in environmentally friendly production processes is discussed. The book is intended for biologists with an interest in environmental microbiological issues, but also for students of process or environmental engineering, geoecology or geology, as well as students of other environmental science disciplines. For the 3rd edition, the authors have completely revised, corrected, updated and supplemented the book.
Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications. Presents tools, connections and proactive solutions to take sustainability programs to the next level Offers a practical guide for making students proficient in modern electronic data analysis and graphics Provides knowledge and background to develop specific platforms related to environmental sensing, including control water, air and soil quality, water and wastewater treatment, desalination, pollution mitigation/control, and resource management and recovery
The bestselling reference on environmental microbiology—now in a new edition This is the long-awaited and much-anticipated revision of the bestselling text and reference. Based on the latest information and investigative techniques from molecular biology and genetics, this Second Edition offers an in-depth examination of the role of microbiological processes related to environmental deterioration with an emphasis on the detection and control of environmental contaminants. Its goal is to further our understanding of the complex microbial processes underlying environmental degradation, its detection and control, and ultimately, its prevention. Features new to this edition include: A completely new organization with topics such as pathogens in developing countries, effects of genetically modified crops on microbial communities, and transformations of toxic metals Comprehensive coverage of key topics such as bacteria in the greenhouse and low-energy waste treatment New coverage relating core book content to local, regional, and global environmental problems Environmental Microbiology, Second Edition is essential reading for environmental microbiologists and engineers, general environmental scientists, chemists, and chemical engineers who are interested in key current subjects in environmental microbiology. It is also appropriate as a textbook for courses in environmental science, chemistry, engineering, and microbial ecology at the advanced undergraduate and graduate levels.
This book focuses on successful application of microbial biotechnology in areas such as medicine, agriculture, environment and human health.
Microorganisms are ubiquitous on earth. These microorganisms are able to perform various functions in the environment. Microbial applications are used as biofertilizers, bioremediation, biofortification and other sustainable approaches of environmental development. Indigenous microbial cultures have the potential to perform various functions that are beneficial to achieve the sustainable goals. To date, different strains have been commercialized for the industrial and common applications for the sustainable environment. This book will cover different aspects of microbial technology for sustainable development.
A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms. Helps biologists succeed in understanding the concepts of Artificial Intelligence and machine learning Equips with new data mining strategies an easy interface into the world of Artificial Intelligence Enables researchers to enhance their own sphere of researching Artificial Intelligence