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Chapter

Cover Introduction to Bioinformatics

Introduction to systems biology  

This chapter describes systems biology. The key idea of systems biology is integration. Indeed, an initial goal of systems biology is to identify the active networks in cells, organisms, and ecosystems, and to understand the properties of their components and the interactions among them. The integrated activities of components of cells depend on networks of interactions. The chapter then looks at the general features of graphs, and the representation of networks by graphs. It considers which kinds of biological interaction patterns can profitably be thought of as networks. The chapter also identifies the distinction between static and dynamic properties of networks, before assessing the concepts of entropy and complexity and how to apply them to biological data. Finally, it outlines the properties of the Burrows-Wheeler transform and its applications.

Chapter

Cover Core Maths for the Biosciences

Extension: dynamical systems  

This chapter focuses on dynamical systems, wherein the simplest nonlinear mathematical models could give rise to incredibly complex behaviour. It mentions scientists studying biological and physical processes of nature that were in the forefront of the revolution in mathematics for discovering dynamical systems. It also introduces some basic concepts of complexity theory: equilibria and stability, bifurcations, and chaos. The chapter begins with a brief snapshot of the birth of chaos theory, particularly theories of pattern formation and ecological implications. It cites the truncation error, which is another source of error in numerical methods that happens by approximating the true function by a Taylor series that is truncated after the first two or three terms.

Chapter

Cover Origins of Biodiversity

Does evolution make everything bigger and better?  

This chapter examines the importance of studying the evolution of size and complexity. Trends in the fossil record can provide an informative view of evolutionary change over time, but they can often be interpreted in a number of different ways. The evolution of horses, which has long been a classic case of an evolutionary trend in size and specialization, provides a convenient illustration of the influence of data incompleteness on views of evolutionary change. Proposed explanations for 'Cope's rule' (increase in body size) include microevolutionary advantage to larger individuals, macroevolutionary advantage to lineages with larger size in diversifying or avoiding extinction, and stochastic (undirected) evolution of body size resulting in an overall increase in the maximum size over time. Meanwhile, complexity is hard to define and measure. The chapter then presents a case study on whether biodiversity has increased over time.