1 The Zero-Force Evolutionary Law 2 Randomness, Hierarchy, and Constraint 3 Diversity 4 Complexity 5 Evidence, Predictions, and Tests 6 Philosophical Foundations 7 Implications.

What is life? For four centuries, it has been believed that the only possible scientific approach to this question proceeds from the Cartesian metaphor -- organism as machine. Therefore, organisms are to be studied and characterized the same way "machines" are; the same way any inorganic system is. Robert Rosen argues that such a view is neither necessary nor sufficient to answer the question. He asserts that life is not a specialization of mechanism, but rather a sweeping generalization of it. (...) Above all, Rosen argues that renouncing mechanism does not mean abandoning science. A radical alternative is proposed, drawn equally from experience in biology, physics, and mathematics; an alternative which draws attention to a new class of complex systems, which are radically different from mechanism. (shrink)

"Legend is overdue for replacement, and an adequate replacement must attend to the process of science as carefully as Hull has done. I share his vision of a serious account of the social and intellectual dynamics of science that will avoid both the rosy blur of Legend and the facile charms of relativism.... Because of [Hull's] deep concern with the ways in which research is actually done, Science as a Process begins an important project in the study of science. It (...) is one of a distinguished series of books, which Hull himself edits."—Philip Kitcher, Nature "In Science as a Process, [David Hull] argues that the tension between cooperation and competition is exactly what makes science so successful.... Hull takes an unusual approach to his subject. He applies the rules of evolution in nature to the evolution of science, arguing that the same kinds of forces responsible for shaping the rise and demise of species also act on the development of scientific ideas."—Natalie Angier, New York Times Book Review "By far the most professional and thorough case in favour of an evolutionary philosophy of science ever to have been made. It contains excellent short histories of evolutionary biology and of systematics (the science of classifying living things); an important and original account of modern systematic controversy; a counter-attack against the philosophical critics of evolutionary philosophy; social-psychological evidence, collected by Hull himself, to show that science does have the character demanded by his philosophy; and a philosophical analysis of evolution which is general enough to apply to both biological and historical change."—Mark Ridley, Times Literary Supplement "Hull is primarily interested in how social interactions within the scientific community can help or hinder the process by which new theories and techniques get accepted.... The claim that science is a process for selecting out the best new ideas is not a new one, but Hull tells us exactly how scientists go about it, and he is prepared to accept that at least to some extent, the social activities of the scientists promoting a new idea can affect its chances of being accepted."—Peter J. Bowler, Archives of Natural History "I have been doing philosophy of science now for twenty-five years, and whilst I would never have claimed that I knew everything, I felt that I had a really good handle on the nature of science, Again and again, Hull was able to show me just how incomplete my understanding was.... Moreover, [Science as a Process] is one of the most compulsively readable books that I have ever encountered."—Michael Ruse, Biology and Philosophy. (shrink)

Recent observations of power-law distributions in the connectivity of complex networks came as a big surprise to researchers steeped in the tradition of random networks. Even more surprising was the discovery that power-law distributions also characterize many biological and social networks. Many attributed a deep significance to this fact, inferring a “universal architecture” of complex systems. Closer examination, however, challenges the assumptions that (1) such distributions are special and (2) they signify a common architecture, independent of the system's specifics. The (...) real surprise, if any, is that power-law distributions are easy to generate, and by a variety of mechanisms. The architecture that results is not universal, but particular; it is determined by the actual constraints on the system in question. BioEssays 27:1060–1068, 2005. © 2005 Wiley Periodicals, Inc. (shrink)

The writings of Joseph Henry Woodger (1894–1981) are often taken to exemplify everything that was wrongheaded, misguided, and just plain wrong with early twentieth-century philosophy of biology. Over the years, commentators have said of Woodger: (a) that he was a fervent logical empiricist who tried to impose the explanatory gold standards of physics onto biology, (b) that his philosophical work was completely disconnected from biological science, (c) that he possessed no scientific or philosophical credentials, and (d) that his work was (...) disparaged – if not altogether ignored – by the biologists and philosophers of his era. In this paper, we provide the first systematic examination of Woodger’s oeuvre, and use it to demonstrate that the four preceding claims are false. We argue that Woodger’s ideas have exerted an important influence on biology and philosophy, and submit that the current consensus on his legacy stems from a highly selective reading of his works. By rehabilitating Woodger, we hope to show that there is no good reason to continue to disregard the numerous contributions to the philosophy of biology produced in the decades prior to the professionalization of the discipline. (shrink)

Our understanding of how evolution acts on biological networks remains patchy, as is our knowledge of how that action is best identified, modelled and understood. Starting with network structure and the evolution of protein–protein interaction networks, we briefly survey the ways in which network evolution is being addressed in the fields of systems biology, development and ecology. The approaches highlighted demonstrate a movement away from a focus on network topology towards a more integrated view, placing biological properties centre‐stage. We argue (...) that there remains great potential in a closer synergy between evolutionary biology and biological network analysis, although that may require the development of novel approaches and even different analogies for biological networks themselves. (shrink)

This collection broadens the scientific discussion of modularity by bringing together experts from a variety of disciplines, including artificial life, ...

The Development of Modern Taxonomy Taxonomy has a long history, going back to the ancient Greeks and to forerunners even less sophisticated in systematics. Our interest here is centered on modern taxonomy itself, and we shall largely ...

Compiling twenty articles on the nature of life and on the objective of the natural sciences, this remarkable book complements Robert Rosen's groundbreaking Life Itself--a work that influenced a wide range of philosophers, biologists, linguists, and social scientists. In Essays on Life Itself, Rosen takes to task the central objective of the natural sciences, calling into question the attempt to create objectivity in a subjective world and forcing us to reconsider where science can lead us in the years to come.

Recent observations of power-law distributions in the connectivity of complex networks came as a big surprise to researchers steeped in the tradition of random networks. Even more surprising was the discovery that power-law distributions also characterize many biological and social networks. Many attributed a deep significance to this fact, inferring a “universal architecture” of complex systems. Closer examination, however, challenges the assumptions that (1) such distributions are special and (2) they signify a common architecture, independent of the system's specifics. The (...) real surprise, if any, is that power-law distributions are easy to generate, and by a variety of mechanisms. The architecture that results is not universal, but particular; it is determined by the actual constraints on the system in question. BioEssays 27:1060–1068, 2005. © 2005 Wiley Periodicals, Inc. (shrink)

We survey some of the concepts, methods, and applications of community detection, which has become an increasingly important area of network science. To help ease newcomers into the field, we provide a guide to available methodology and open problems, and discuss why scientists from diverse backgrounds are interested in these problems. As a running theme, we emphasize the connections of community detection to problems in statistical physics and computational optimization.