Artificial Intelligence in Microbiology: Scope and Challenges volume-II

1st Edition, Volume 56 - January 24, 2025
Imprint: Academic Press
Editors: Akanksha Srivastava, Vaibhav Mishra
Language: English
Hardback ISBN:
9 7 8 - 0 - 4 4 3 - 2 9 6 2 6 - 0
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 2 9 6 2 7 - 7

Artificial Intelligence in Microbiology: Scope and Challenges, Volume-II, Volume 56 covers changes due to the emergence of Artificial Intelligence (AI). AI is being used to analyz… Read more

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Artificial Intelligence in Microbiology: Scope and Challenges, Volume-II, Volume 56 covers changes 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, and more. Chapters include Taking on the resistance: AI and battle against antimicrobial resistance, AI-powered insights into microbial communities for bioremediation strategies, Efficient and cost-effective production of viral vaccines via AI, Production and development of novel drug targets through AI, Use of AI in neuroscience, Role of Artificial Intelligence in studying metagenomics of Microbes: Decoding the microbial Sphere, and more.

Other chapters explore Exploring the functional role of bacterial proteins via AI, Application of AI in Aquaculture/Fisheries: Disease identification, detection, diagnosis, drug development, Artificial Intelligence in drug discovery & development; scope and challenges, Production of bacteriocins by AI: as food preservative, Exploring the Role of Artificial Intelligence in the Microbial remediation of heavy metals, Uses of Artificial Intelligence in the Agricultural Pest Management, Microbial fermentation processes using Artificial Intelligence, and more.

Artificial Intelligence in Microbiology: Scope and Challenges Volume 2
Cover image
Title page
Table of Contents
Recent Titles In The Series
Copyright
Contributors
Preface
Chapter One Taking on the resistance_ Artificial intelligence (AI) and battle against antimicrobial resistance
Abstract
Keywords
1 Introduction
2 Antimicrobial resistance_ Mechanisms and prevalence
3 AI application #1: Extracting compounds of value
3.1 Artificial intelligence and unfolding proteins
4 AI application #2: Drug development and creating new antimicrobials
5 AI application #3: Predicting side-effects
6 AI application #4: Developing drugs to reduce biofilms on drug delivery systems
7 AI application #5: Detecting disease likelihood
8 AI application #6: Machine learning to identify the likelihood of gene transfer as an antibiotic resistance mechanism
9 AI application #7: Pathogen biogeography and AI
10 Machine learning approaches to support such inquiries include
11 Summary
References
Chapter Two Production of bacteriocins by AI: As food preservative
Abstract
Keywords
1 Introduction
1.1 Optimising AI for the fermentation process and training AI-algorithms in screening and identifying bacteriocin-producing strains
1.2 Involvement of multiple steps using AI for bacteriocin production
1.3 Using AI for quality control to ensure standing of using bacteriocin
1.4 Advantages and limitations of using AI for bacteriocins
2 Future of using bacteriocins by AI as food preservative agent
3 Conclusion
Conflict of interest
References
Chapter Three Artificial intelligence (AI) implementation in the food industry as a promising tool for protecting food from microbes
Abstract
Keywords
1 Introduction
2 Application of artificial intelligence (AI) in food industry
2.1 Importance of artificial intelligence (AI) in sorting of packages and products
2.2 Artificial intelligence (AI) in object recognition and classification
2.3 Artificial intelligence (AI) in automated packaging
2.4 Artificial intelligence (AI) in predicting shelf life
2.5 Maintaining cleanliness
2.6 Artificial intelligence (AI) in developing new products
2.7 Assisting customers with decision making
2.8 Artificial intelligence in food processing and distribution
2.9 Supply Chain Optimization
3 Improving Food Safety Using Artificial Intelligence
3.1 Food Spoilage Detection
3.2 Food Preservation Techniques
3.3 Smart Food Life Prediction
3.4 AI Techniques Used for Improving Food Quality and Safety
4 Artificial Intelligence Systems and for Enhancing the Public Health
5 Artificial intelligence's Role in Alleviating Food Insecurity and Waste Management
5.1 Prospects of the AI in Food Security
5.2 AI and Food Waste Management
6 Challenges and Limitations of Applying AI in Food Sector
7 The Future Application of Artificial Intelligence in the Food Industry
References
Chapter Four Artificial intelligence and microbial cellular intelligence for bioprocess and biofuel
Abstract
Keywords
1 Introduction
1.1 Microbial cellulose
1.2 Microbial hemicellulose
1.3 Advanced AI tools and microbial lignin
2 Pretreatment
3 Biofuel types
4 Artificial intelligence (AI) and biofuel production
4.1 Bioethanol
4.2 Biohydrogen
4.3 Biomethane
4.4 Biobutanol
4.5 Bio-diesel
5 Recent advancement in scale up fermentation
6 Role of artificial intelligence in microbial fermentation for biofuel
7 Future prospects of AI in microbial biofuel
8 Conclusions
Acknowledgements
References
Chapter Five The power of AI in viral vaccine production: A paradigm shift in efficiency and costs
Abstract
Keywords
1 Introduction
2 Vaccine victories: The timeline
3 AI in vaccine development
3.1 Reverse vaccination (RV)
4 Unlocking breakthroughs: AI's role in revolutionizing COVID-19 vaccine discovery
4.1 Utilizing AI for efficient data collection in COVID-19 vaccine research
4.2 Different approach utilizes for COVID-19 vaccine discovery
4.3 Different algorithms used for the vaccine discovery
4.4 AI advances post-marketing vaccine surveillance
4.5 AI revolutionizes vaccine development for Disease X
4.6 Critical initiative for Disease X vigilance
5 Limitations of AI-assisted vaccine development
6 Conclusion and future prospectus
References
Chapter Six Role of artificial intelligence in studying metagenomics of microbes: Decoding the microbial sphere
Abstract
Keywords
1 Introduction
2 Metagenomics
3 Metagenomic approaches/data types
3.1 Targeted metagenomics via amplicon sequencing/DNA-metabarcoding
3.2 Untargeted met genomics via Shotgun sequencing
3.3 Re-analysed metagenomics
4 Metagenomics data (metdata) and challenges in its handling
5 Artificial intelligence (AI): An efficient way to handle metadata
5.1 Machine learning (ML): Understanding the microbial code
6 AI tools for metadata analysis
7 Challenges to implementing AI and ML in metadata analysis
7.1 Bacterial data heterogeneity analysed by metadata
7.2 Data representation
7.3 Taxonomy and classification
7.4 Model integration
8 AI in food and environmental microbiological metadata
9 AI in health sciences metadata
10 AI in plant growth promoting bacteria metagenomics
11 Future prospects
References
Chapter Seven Revolutionizing bioethanol production: The role of AI in process innovation
Abstract
Keywords
1 Introduction
2 What is Artificial Intelligence (AI)?
3 Classification of feedstocks for bioethanol production
3.1 Integration of AI in first-generation feedstock
3.2 Second-generation feedstock and AI
3.3 Involvement of AI in third-generation feedstock
3.4 AI and fourth-generation feedstock
4 Harnessing of divergent microorganisms as a source for bioethanol production
4.1 Fungal strains in bioethanol production
5 Genetically modified microorganisms
6 AI application in bioethanol production stages
7 Enzymes used in hydrolysis
8 AI in fermentation and recovery
9 Conclusions and future perspective
References
Chapter Eight AI in infectious disease diagnosis and vaccine development
Abstract
Keywords
1 Introduction
1.1 AI in healthcare
2 Infectious-disease diagnostics and treatments
2.1 Enhancing diagnostic accuracy
2.2 Predicting infectious disease outbreaks
2.3 Facilitating personalized treatments
2.4 Ethical and regulatory challenges
3 AI-driven vaccine models for infectious diseases
3.1 VaxELAN
3.2 Vaxi-DL
4 nHLAPred tool for MHC class-I prediction
4.1 B-cell epitope prediction tools for infectious diseases
4.2 T-cell epitope prediction tool for infectious disease
4.3 Application of AI techniques in vaccine development for various infectious diseases
5 Advances in AI for infectious-disease surveillance
6 Conclusion
7 Future directions
Acknowledgement
References
Chapter Nine Harnessing artificial intelligence in identifying and isolation of marine peptides
Abstract
Keywords
1 Introduction
2 Diverse structures and therapeutic potentials of marine-derived peptides
2.1 Impact of artificial intelligence (AI) on bioactive peptides from marine bacteria
2.2 AI and ML in isolating and analysing bioactive peptides from Cyanobacteria
2.3 Bioactive peptides from fungal sources
2.4 Bioactive peptides from other marine sources
2.5 Use of artificial intelligence (AI) and their different models to make easier process of marine bioactive peptides from phylum Porifera
3 Overall impact of artificial intelligence (AI) on microbial peptides
3.1 Procedure involved in peptide discovery employing artificial intelligence (AI) model
4 Different machine learning (ML) models for marine peptide analysis
4.1 k-nearest neighbour (kNN) for marine peptide interpretation
4.2 Random forest (RF): Advancing marine peptide research
4.3 Artificial neural network (ANNs) in marine peptides
4.4 Utilising a machine learning (ML) model support vector machine (SVM) for marine peptide analysis
5 Application of different deep learning (DL) model in marine peptide analysis
5.1 Leveraging adaptive neuro-fuzzy inference system (ANFIS) to anti microbial peptide from marine
6 Conclusions and future prospects
References
Chapter Ten AI-based advances in crop disease detection and health improvement
Abstract
Keywords
1 Introduction
2 AI techniques in crop health management
3 ML models for crop improvement
4 Crop breeding by AI model
5 Monitoring system for plant health by AI
6 Crop's disease detection
7 Microbiome analysis through AI
8 Synthetic community analysis by AI
9 Functional annotation by AI
10 Conclusion
References
Chapter Eleven The role of AI in microbial fermentation: Transforming industrial applications
Abstract
Keywords
1 Introduction
2 AI application in the food industries
3 AI applications in the alcohol and beverage industries
4 AI application in the pharmaceutical industries
5 Conclusion
References
Chapter Twelve Artificial intelligence and neurological health
Abstract
Keywords
1 Background
2 AI in the healthcare system
3 AI in neurosciences
4 AI in epilepsy
5 AI in psychology
6 AI in seizure disorders
7 AI in stroke
8 AI in neuro-oncology
9 AI in neuro-traumatology
10 AI in meningitis
11 AI/ML applications in CNS drug discovery
12 Conclusion
References
Further reading
Chapter Thirteen Enhancing microbiology with artificial intelligence_ Future of disease detection and treatment
Abstract
Keywords
1 Introduction
2 AI programmed image analysis for diagnosis
3 AI increasing accuracy and workflow speed
4 Analysis of pathogen genome sequencing by AI
5 Patient testing with AI powered devices
6 AI in microbial epidemiological studies
7 Personalized therapy
8 Future outlook
9 Conclusion
References
Chapter Fourteen Application of artificial intelligence (AI) in aquaculture/fisheries: Microbial disease identification and diagnosis
Abstract
Keywords
1 Introduction
2 Need for artificial intelligence (AI) in fisheries and aquaculture
2.1 Precision management via artificial intelligence (AI)
2.2 Monitoring and surveillance via artificial intelligence (AI)
2.3 Artificial intelligence (AI) in aquatic animal health management
2.4 Artificial intelligence (AI) in species identification
2.5 Artificial intelligence (AI) in fish breeding programmes
3 Advanced artificial intelligence (AI) based sensors used in aquaculture/fisheries
4 Advanced artificial intelligence (AI) based drones used in aquaculture/fisheries
5 Artificial intelligence (AI) based early microbial disease detection, diagnosis and monitoring approaches in fisheries/aquaculture
5.1 Image-processing technology
6 Intelligent techniques to detect the fish infections
6.1 Surface injury recognition
6.2 Diagnosis of internal tissues through microscopic pictures
6.3 Pathogen recognition through spectral pictures
6.4 Parasite diagnosis through ultrasonic pictures
6.5 Pathogen diagnosis through fluorescence pictures
6.6 Indirect diagnosis through electrochemical sensors
7 Commonly occurred microbial diseases in aquaculture
7.1 Bacterial diseases
7.2 Viral diseases
7.3 Fungal diseases
8 Future perspective
9 Conclusion
References
Chapter Fifteen Artificial intelligence in plant disease mitigation and nutrient acquisition
Abstract
Keywords
1 Introduction
2 Role of AI in soil health and plant nutrition
2.1 Application of AI and ML algorithms in nutrient management and fertilizer recommendation
2.2 Image recognition by machine learning (ML)
2.3 Image recognition by deep learning (DL)
3 Deep learning (DL) based plant lesion and plant disease detection system
4 Convolutional neural networks (CNNs)
4.1 The CNNs-applications in plant disease detection and based predictive approaches for diagnosing the plant diseases and pests
5 Assessment of conventional strategies for the recognition of plant illness and pests
6 Plant–microbe interaction identification with AI methodologies
7 Agricultural crop disease detection with AI models
8 Plant disease detection: Issues and challenges
9 Issues in plant disease detection
10 Challenges and future considerations
11 Conclusion
References
Further reading
Chapter Sixteen AI-driven antimicrobial peptides for drug development
Abstract
Keywords
1 Introduction
2 AI applications
2.1 Simulation techniques based advancing drug discovery
3 Advancements in AI/ML
3.1 Application of computational methods in drug designing
3.2 Specific AI models for microbial drug discovery
4 Combatting antimicrobial resistance
5 AI's role in for target identification
5.1 Antimicrobial peptide (AMP) engineering via AI
6 AI-driven AMP discovery: Key terms and techniques
6.1 Ethical considerations
6.2 Challenges and future directions
References

Akanksha Srivastava

Dr. Akanksha Srivastava is currently a Research Scientist in the Department of Microbiology, Institute of Medical Science, Banaras Hindu University, Varanasi, India. She earned her PhD in Life Science from the Academy of Scientific and Industrial Research (AcSIR), CSIR-Central Drug Research Institute (CSIR-CDRI), Lucknow. Her expertise is in microbiology, fermentation technology, and virology. She was a recipient of the Young Women Scientist fellowship award from DST in the WOS-A scheme and previously received the ICMR- Research Associate and Senior Research Fellowship awards. She is a reviewer for several reputed international peer-reviewed journals. She has published numerous research papers in acclaimed journals, has authored one book, book chapters, as well as review articles. She was recognized for excellence in research by the Honorable Chief Minister of Uttar Pradesh, India, the SGBRD Society, and the SIEBS Society. Her international collaborations include researchers in Israel, United Kingdom, United States, and Finland.

Affiliations and expertise

Research Scientist, Department of Microbiology, Institute of Medical Science, Banaras Hindu University, Varanasi, India

Vaibhav Mishra

Dr. Vaibhav Mishra is currently an Assistant Professor-III at the Institute of Microbial technology, Amity University, U. P. India. He earned his PhD in Applied Microbiology from Banaras Hindu University, Varanasi, India. His expertise in microbiology and gastroenterology. He was previously a Post-Doctoral Researcher in the Department of Neurology at the University of Missouri in Columbia, Missouri, USA. Before joined University of Missouri, He worked as Senior Research Associate at the University of Johannesburg, South Africa. Dr. Mishra was selected as one of the twelve young biomedical scientists for the prestigious 2019 preceptorship program in Seoul, South Korea among all over young scientists of Asia. In the same year, he was also elected as a Fellow of the Environmental & Biological society (FEBS), one of the most esteemed and oldest societies of India. Moreover, he was the recipient of the “Young Scientist Award” in 2017 by ISGBRD for excellent performance in research. Dr. Mishra is the Assistant Editor of Environmental Sustainability and serves as a reviewer for several reputed international peer-reviewed journals. He has published many research papers in acclaimed journals and has authored two books, book chapters as well as review articles.

Affiliations and expertise

Assistant Professor, Institute of Microbial Technology, Amity University, U. P. India

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