A Biologist’s Guide to Artificial Intelligence

Building the foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences

1st Edition - February 29, 2024
Editors: Ambreen Hamadani, Nazir A Ganai, Hamadani Henna, J Bashir
Language: English
Paperback ISBN:
9 7 8 - 0 - 4 4 3 - 2 4 0 0 1 - 0
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 2 4 0 0 0 - 3

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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.

Cover image
Title page
Table of Contents
Copyright
Contributors
Chapter 1. Exploring artificial intelligence through a biologist's lens
Introduction
Machine learning algorithms—the foundations of AI
Integrating AI with biological science
Research challenges
Conclusion
Chapter 2. The synergy of AI and biology: A transformative partnership
Introduction
The transformative power of AI in biology
The need for AI in biology
Some applications
Conclusion
Chapter 3. Understanding life and evolution using AI
Introduction
AI algorithms and techniques
Significance of AI in biology
Conclusion
Chapter 4. Decoding life: Genetics, bioinformatics, and artificial intelligence
Introduction
Genetics: Bioinformatics and artificial intelligence interface
Bioinformatics: a boon for new-age genetics research
Artificial intelligence in biological research
AI and ML in plant breeding
Using AI to study biochemical phenotype
How does AI aid crop improvement efforts by changing the breeding paradigm?
Machine learning for biochemical phenotypes
Machine learning for genomic prediction
Potential applications of AI and ML in classical and modern plant breeding
Application of AI in phenomics
Application of ML in image processing
Research challenges
Conclusion
Chapter 5. AI in healthcare: Pioneering innovations for a healthier tomorrow
Introduction
Technological advancement
How is AI used in healthcare?
Applications of artificial intelligence in healthcare
Conclusion
Chapter 6. Reimagining occupational health and safety in the era of AI
Introduction
Understanding the application of AI/ML in workplace safety through vision algorithms
Workplace exposure assessment of toxic gases using AI techniques
Workplace exposure assessment of hazardous chemicals using AI techniques
AI for diagnostic and prevention of occupational lung diseases
NLP utility for workplace health education and awareness
Chapter 7. From data to insights: Leveraging machine learning for diabetes management
Introduction
Understanding data collection and preprocessing of diabetes-related data
Machine learning models for diabetes risk prediction
Predictive modeling for blood glucose monitoring
Ethical considerations in machine learning for diabetes
Conclusion
Chapter 8. Smiles 2.0: The AI dentistry frontier
Introduction
Applications of AI in dentistry
Ethical considerations
Future scope
Conclusion
Chapter 9. Applications and impact of artificial intelligence in veterinary sciences
Introduction
Big data in veterinary sciences
AI in diagnoses
AI for disease prediction and surveillance
Veterinary precision medicine
Robots in veterinary sciences
AI and the future of veterinary medicine
Conclusion
Abbreviations
Chapter 10. Advancing precision agriculture through artificial intelligence: Exploring the future of cultivation
Introduction
Need for AI in precision agriculture
Application of AI in precision agriculture
Benefits of precision agriculture using AI
Challenges and considerations
Conclusion
Abbreviations
Chapter 11. Artificial intelligence in animal farms for management and breeding
Introduction
AI and big data in livestock farms
Identification of animals
Animal monitoring
Disease detection and prevention
Precision nutrition and feed management
Automation for precision farming
Genetic improvement and breeding
Decision support systems
Improving animal production using AI
Conclusion
Chapter 12. Food manufacturing, processing, storage, and marketing using artificial intelligence
Introduction
Challenges of AI in food industry
Future directions of AI in food industry
Ethical considerations, data privacy concerns, and potential biases
Recommendation for future research
Chapter 13. Use of AI in conservation and for understanding climate change
Introduction
Ecological modeling
Biodiversity monitoring and conservation
Climate change
Use of AI in smart farming through the Internet of Things
Conclusion
Chapter 14. Artificial intelligence in marine biology
Introduction
Marine biology, a quick overview
Big data and marine biology
Artificial intelligence in marine science
Challenges and future directions
Conclusion
Chapter 15. Advances in robotics for biological sciences
Introduction
Principles and features of robotics
Advancements and contributions—A review
The foreseeable future
Robot uprising, is it possible?
Challenges
Approval and authentication
Conclusion
Chapter 16. Robotics and computer vision for health, food security, and environment
Introduction
Conclusion
Chapter 17. Artificial intelligence in classrooms: How artificial intelligence can aid in teaching biology
Introduction
AI educational tools
Criticisms of AI educational tools
Conclusion
Abbreviations
Chapter 18. Ethical issues around artificial intelligence
Overview of artificial intelligence
Machine learning
Some ethical issues around artificial intelligence
Global efforts to mitigate the challenges of ethical issues around AI
Ethical implications of AI-powered surveillance
Challenges of explainability in AI systems
AI automation and its effects on employment
Ethical concerns surrounding AI-powered autonomous weapons
AI-enabled manipulation techniques and their impacts
Ethical decision-making and values
Conclusion
Abbreviations
Chapter 19. A meshwork of artificial intelligence and biology: The future of science
Introduction
Big data in biology and the role of AI
AI for rapid breakthroughs in biology
The promise of AI in biology
Alignment of AI with trends in biological sciences
Science fiction and AI
The future of the meshwork
Research challenges involved
Cautious steps forward
Conclusion
Index

Ambreen Hamadani

Dr Ambreen Hamdani (BVSc & AH, MVSc, PhD) is currently a Post Doctoral Fellow at the National Institute of Technology, Srinagar. Her PhD work was centred around the use of Artificial Intelligence for the prediction of genetic merit in Animals. She has published more than a hundred papers and a book. She has also won more than 30 international and national awards including (DST, Lockheed Martin, Tata Trust) India Innovation Growth Program 2019, National level elocution and writing contests, debating contests, the young scientists award for best scientific presentation etc. She has been granted a copyright and has published a patent as well. She has also been selected for a post-doctoral fellowship at the University of Wisconsin-Madison, USA.

Affiliations and expertise

Post Doctoral Fellow, National Institute of Technology, Srinagar, India

Nazir A Ganai

Prof. Nazir Ahmad Ganai (BVSc, MVSc, PhD, PDF) is currently serving as the vice chancellor of Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, India. He acquired his PhD from the National Dairy Research Institute, India in animal genetics and breeding. He has also completed multiple postdoctoral fellowships at Wageningen University, The Netherlands, University of Wisconsin, Madison, USA, and the Durham University, UK. He has authored more than a hundred publications and a book. He has been awarded extramural grants worth millions of dollars for the Institutes he served including the 30 crore World Bank Funded National Agricultural Higher Education Project. He is also the recipient of the Indian National Science Academies’ Best Teacher Award, 2019. Dr Ganai has a teaching and research experience of more than 28 years. He was a part of the research team that developed Noorie, the world’s first pashmina Goat clone.

Affiliations and expertise

Vice Chancellor, Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir, India

Hamadani Henna

Dr Henna Hamadani (B.V.Sc. & A.H., M.V.Sc., PhD) is currently working as Assistant Professor cum Junior Scientist in the Faculty of Veterinary Sciences and Animal Husbandry, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir. She graduated in Veterinary Sciences and Animal Husbandry from SKUAST-K and completed her master’s and PhD degrees in Livestock Production and Management. She is the recipient of the Department of Science and Technology, INSPIRE fellowship of Govt. of India. She has worked in the area of Artificial Intelligence during her Summer Research Fellowship granted by Indian National Science Academy. She has many awards and publications to her name including young scientist awards, best scientific presentation awards etc. She has carried out pioneering work on the characterization and documentation of India’s first and only registered geese breed the Kashmir Anz

Affiliations and expertise

Assistant Professor, Faculty of Veterinary Sciences and Animal Husbandry, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir.

J Bashir

Dr Janibul Bashir received his B. Tech. degree in Information Technology from the National Institute of Technology Srinagar and his PhD degree in Computer Science from the Indian Institute of Technology Delhi. He is currently an Assistant Professor in the Department of Information Technology at the National Institute of Technology Srinagar. He has previously worked at Samsung Research India Bangalore as a software engineer. He is also a visiting faculty at Atal Bihari Vajpayee-Indian Institute of Information Technology and Management (ABV-IIITM), Gwalior. Dr Janib is also a gold medallist in Btech. Dr Bashir is working on the application of artificial intelligence, machine learning and its applications in Information Technology. The research works authored by Dr Janibul Bashir have received several honours, including a Best Paper nomination at NOCS 2020. He has also published 2 patents

Affiliations and expertise

Assistant Professor, National Institute of Technology, Srinagar, India

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A Biologist’s Guide to Artificial Intelligence

Building the foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences

Purchase options

Save 50% on book bundles

Institutional subscription on ScienceDirect

Ambreen Hamadani

Nazir A Ganai

Hamadani Henna

J Bashir