Chapter 1: Introduction to Quantitative Biology.- Chapter 2: Architectonics of the Cell.- Chapter 3: Mechanics of the Cell.- Chapter 4: Implementing Toy Models in Microsoft Excel.- Chapter 5: Implementing Toy Models in Python.- Chapter 6: Differential Equations to Describe Temporal Changes.- Chapter 7: Diversity of the Cell.- Chapter 8: Randomness, diffusion, and probability.- Chapter 9: Self-Organization of the Cell.- Chapter 10: Modeling feedback regulations Chapter 11: Development of the Cell over Time (Perspectives).
Akatsuki Kimura is a Professor at National Institute of Genetics and The Graduate University for Advanced Studies (SOKENDAI), Japan. He earned his Bachelor under the supervision of Dr. Masayuki Yamamoto, and his PhD under the supervision of Dr. Masami Horikoshi, in Biophysics and Biochemistry from the University of Tokyo. After completing his PhD, Kimura joined the field of quantitative biology as an assistant professor at Keio University and a JSPS (Japan Society for the Promotion of Science) fellow under the supervision of Dr. Shuichi Onami. In 2006, Kimura launched his research group, Cell Architecture Laboratory, at National Institute of Genetics as an Associate Professor. He was also appointed at The Graduate University for Advanced Studies (SOKENDAI). His research interest is to construct mechanical models of the cell, to understand the mechanics, diversity, and self-organization of the cell.
This textbook is for biologists, to conduct quantitative analysis and modeling of biological processes at molecular and cellular levels.
Focusing on practical concepts and techniques for everyday research, this text will enable beginners, both students and established biologists, to take the first step in quantitative biology. It also provides step-by-step tutorials to run various sample programs in one’s personal computer using Excel and Python.
This volume traces topics, starting with an introductory chapter, such as modeling, construction and execution of numerical models, and key concepts in quantitative biology: feedback regulations, fluctuations and randomness, and statistical analyses. It also provide sample codes with guidance to procedure programming for actual biological processes such as movement of the nucleus within a cell, cell-cycle regulation, stripe pattern formation of skins, and distribution of energy.
Written by a leading research scientist who has a background in biology, studied quantitative approaches by himself, and teaches quantitative biology at several universities, this textbook broadens quantitative approaches for biologists who do not have a strong background in mathematics, physics, or computer programming, and helps them progress further in their research.