This volume reviews examples and notions of robustness at several levels of biological organization. It tackles many philosophical and conceptual issues and casts an outlook on the future challenges of robustness studies in the context of a practice-oriented philosophy of science. The focus of discussion is on concrete case studies. These highlight the necessity of a level-dependent description of robust biological behaviors.Experts from the neurosciences, biochemistry, ecology, biology, and the history and the philosophy of life sciences provide a multiplex perspective on the topic. Contributions span from protein folding, to cell-level robustness, to organismal and developmental robustness, to sensorimotor systems, up to the robustness of ecological systems.Several chapters detail neurobiological case-studies. The brain, the poster child of plasticity in biology, offers multiple examples of robustness. Neurobiology explores the importance of temporal organization and multiscalarity in making this robustness-with-plasticity possible. The discussion also includes structures well beyond the brain, such as muscles and the complex feedback loops involved in the peculiar robustness of music perception. Overall, the volume grounds general reflections upon concrete case studies, opening to all the life sciences but also to non-biological and bio-inspired fields such as post-modern engineering. It will appeal to researchers, students, as well as non-expert readers.
Robustness and Evolvability in Living Systems tackles this perplexing paradox. The book explores why genetic changes do not cause organisms to fail catastrophically and how evolution shapes organisms' robustness.
Robust Design brings together 16 chapters by an eminent group of authors in a wide range of fields presenting aspects of robustness in biological, ecological, and computational systems.
In the first stage, a naı ̈ve variant of the ancestral finch, when in foraging mode, was more inclined than other birds to pick up sharp sticks. This habit spread in the population by Darwinian evolution because those behaving in this ...
But what exactly is the rationale for using the term “machine” to designate macromolecular assemblies? According to Nogales and Grigorieff (2001, F1), “this designation captures many of the aspects characterizing these biological ...
The book provides more realistic stochastic biological system models to mimic the real biological systems in evolutionary process and then introduces network evolvability, stochastic evolutionary game theory and strategy based on nonlinear ...
A New Biology for the 21st Century recommends that a "New Biology" approach-one that depends on greater integration within biology, and closer collaboration with physical, computational, and earth scientists, mathematicians and engineers-be ...
Treating extant mammals, the primary purpose of the proposed work is to provide new perspectives on common themes in the literature on robustness (“functional diversity”; differential resistance to “deconstraint” of conserved ...
Thorough and accessible, this book presents the design principles of biological systems, and highlights the recurring circuit elements that make up biological networks.
This book investigates the relevance of robustness in a modern intelligent computing context, where many systems take inspiration from fundamental problem-solving strategies found in nature such as redundancy, granularity, adaptation, ...
Can it have, or evolve to have, a similar impact in biology? The chapters in this book demonstrate that, indeed, systems and control theoretic concepts and techniques can have a significant impact in systems and synthetic biology.