Artificial Intelligence In Microbial Research
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Artificial Intelligence in Microbial Research
This book explores the convergence of microbiology and artificial intelligence (AI) and delves into the intricate world of microbial systems enhanced by cutting-edge AI technologies. The book begins by establishing a foundation in the fundamentals of microbial ecosystems and AI principles. It elucidates the integration of AI in microbial genomics, demonstrating how advanced algorithms analyze genomic data and contribute to genetic engineering. Bioinformatics and computational microbiology are explored, showcasing AI's role in predictive modeling and computational tools. The intersection of AI and microbial applications extends to drug discovery, precision agriculture, and pathogen detection. Readers gain insights into AI-driven drug development, the optimization of agricultural practices using microbial biostimulants, and early warning systems for crop diseases. The book highlights AI's role in microbial biotechnology, elucidating its impact on bioprocessing, fermentation, and other biotechnological applications. Climate-smart agriculture and microbial adaptations to environmental challenges are discussed, emphasizing sustainable practices. This book caters to a diverse audience including teachers, researchers, microbiologist, computer bioinformaticians, plant and environmental scientists. The book serves as additional reading material for undergraduate and graduate students of computer science, biomedical, agriculture, human science, forestry, ecology, soil science, and environmental sciences and policy makers to be a useful to read.
Artificial Intelligence in Microbiology: Scope and Challenges Volume 1
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
Artificial Intelligence in Pathogenic Microorganism Research
Infections caused by pathogenic microorganisms, including bacteria, viruses, fungi, and other eukaryotic microbes, seriously threaten human health. Traditional research methods and laboratory techniques have many limitations and focus more on the identification and classification of pathogenic microorganisms. In recent years, technologies such as whole genome sequencing and advanced bioinformatics analysis have promoted the research of pathogenic microorganisms. However, with the interplay of multiple factors like global climate change, ecological and environmental changes, urbanization, social behavior, and lifestyle changes, pathogenic microorganisms' transmission patterns and impact scope are gradually changing. There is an urgent need for multidimensional technological approaches to achieve epidemiological monitoring and evolutionary direction prediction of pathogenic microorganisms. Additionally, more robust data processing and analysis capabilities are required for rapid identification and diagnosis, monitoring of drug resistance, development of antimicrobial drugs and vaccines, and optimization of treatment plans. Therefore, Artificial Intelligence (AI) has entered our field of vision. In the field of pathogenic microorganisms, AI has shown tremendous potential. In epidemiological research, AI technology can quickly and automatically collect, integrate and analyze the epidemic data of infectious diseases from different regions, so as to predict the trend and scope of disease transmission, and track the source of infection. In the process of diagnosis and treatment of infectious diseases, machine learning can not only analyze the microscopic images of pathogens, but also analyze the genome sequences of multiple pathogens in a short time, and predict their sensitivity or resistance to specific antibiotics, greatly improving the efficiency and accuracy of diagnosis and treatment of infectious diseases. In drug or vaccine development, researchers can use AI models to predict efficient antigens for diseases such as HIV and influenza, and thus design more effective vaccine candidates. AI models can also analyze the interactions between drugs, pathogens, and patients, in order to design the optimal dosing regimen for each patient. In a word, AI can help human beings better deal with infectious diseases. We welcome original reviews, articles, and other contributions in related fields, which mainly include the following aspects: (1) The application of AI in the differential diagnosis of pathogenic microorganisms (2) The application of AI in the formulation of anti-infection treatment plans (3) The application of AI in monitoring and predicting the prevalence of pathogenic microorganisms (4) Application of AI in the prediction and prevention of infectious diseases caused by pathogenic microorganisms (5) The application of AI in the research and development of anti-infective drugs and vaccines