Developing effective and reliable methods for predictive biology modeling is critical due to its significant economic and societal implications. This is particularly relevant in sectors like pharmacology, agri-food, environmental science, and health research, where accurate modeling drives innovation and decision-making. Unlike traditional computational systems, modeling biological systems requires integrating advanced computer-aided techniques tailored to the complexity of living systems. By addressing these challenges, predictive biology modeling fosters advancements in healthcare, agriculture, and environmental sustainability, ultimately benefiting both industry and academia.
Technical Innovation and Modeling in the Biological Sciences explores the principles and methodologies behind predictive biology modeling, focusing on its application to complex living systems. Through real-world examples, it demonstrates how innovative, computer-aided approaches are transforming fields such as pharmacology, agri-food, environmental science, and health research. Covering topics such as bryological flora, quality cost management, and hepatitis diseases, this book is an excellent resource for biologists, physicians, pharmacologists, bioengineers, computer scientists, professionals, researchers, scholars, academicians, and more.