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As the gateway to scientific thinking, an understanding of the scientific method is essential for success and productivity in science. This book is the first synthesis of the practice and the philosophy of the scientific method. It will enable scientists to be better scientists by offering them a deeper understanding of the underpinnings of the scientific method, thereby leading to more productive research and experimentation. It will also give scientists a more accurate perspective on the rationality of the scientific approach and its role in society. Beginning with a discussion of today's 'science wars' and science's presuppositions, the book then explores deductive and inductive logic, probability, statistics, and parsimony, and concludes with an examination of science's powers and limits, and a look at science education. Topics relevant to a variety of disciplines are treated, and clarifying figures, case studies, and chapter summaries enhance the pedagogy. This adeptly executed, comprehensive, yet pragmatic work yields a new synergy suitable for scientists and instructors, and graduate students and advanced undergraduates.
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Parsimony analysis (cladistics) has long been one of the most widely used methods of phylogenetic inference in the fields of systematic and evolutionary biology. Moreover it has mathematical attributes that lend itself for use with complex, genomic-scale data sets. This book demonstrates the potential that this powerful hierarchical data summarization method also has for both structural and functional comparative genomic research.
Reconstructing the Past seeks to clarify and help resolve the vexing methodological issues that arise when biologists try to answer such questions as whether human beings are more closely related to chimps than they are to gorillas. It explores the case for considering the philosophical idea of simplicity/parsimony as a useful principle for evaluating taxonomic theories of evolutionary relationships. For the past two decades, evolutionists have been vigorously debating the appropriate methods that should be used in systematics, the field that aims at reconstructing phylogenetic relationships among species. This debate over phylogenetic inference, Elliott Sober observes, raises broader questions of hypothesis testing and theory evaluation that run head on into long standing issues concerning simplicity/parsimony in the philosophy of science. Sober treats the problem of phylogenetic inference as a detailed case study in which the philosophical idea of simplicity/parsimony can be tested as a principle of theory evaluation. Bringing together philosophy and biology, as well as statistics, Sober builds a general framework for understanding the circumstances in which parsimony makes sense as a tool of phylogenetic inference. Along the way he provides a detailed critique of parsimony in the biological literature, exploring the strengths and limitations of both statistical and nonstatistical cladistic arguments.
Parsimony is a novel about fathers and sons, about the twisted manifestations of politics and history in the lives of a particular Jewish American family. When the novel opens, David Ansky, a divorced and disaffected New York architect, has gone to Florida to move his father into a local nursing home. He has never been close to the man and dreads the responsibility, intending to dispatch with the matter as swiftly as possible. Yet things do not go as planned, so that quickly he finds himself entangled in the past, trapped in a cat and mouse game with his father in which he is never quite sure how to gauge the man's remarks, which range from the paranoid and sentimental to the cruelly, severely astute. At the heart of this experience is David's reckoning, just after 9/11, with his own life and career, and with his family's radically left-wing past-with his Stalinist grandfather and with his bitter, politically disillusioned father, a Trotsky scholar and retired professor of history. Set in the course of a single day in an apartment overlooking Sanibel Island, the novel explores the generational impact of shattered ideals.
Ockham's razor, the principle of parsimony, states that simpler theories are better than theories that are more complex. It has a history dating back to Aristotle and it plays an important role in current physics, biology, and psychology. The razor also gets used outside of science - in everyday life and in philosophy. This book evaluates the principle and discusses its many applications. Fascinating examples from different domains provide a rich basis for contemplating the principle's promises and perils. It is obvious that simpler theories are beautiful and easy to understand; the hard problem is to figure out why the simplicity of a theory should be relevant to saying what the world is like. In this book, the ABCs of probability theory are succinctly developed and put to work to describe two 'parsimony paradigms' within which this problem can be solved.
The amount of information that can be obtained by using molecular techniques in evolution, systematics and ecology has increased exponentially over the last ten years. The need for more rapid and efficient methods of data acquisition and analysis is growing accordingly. This manual presents some of the most important techniques for data acquisition developed over the last years. The choice and justification of data analysis techniques is also an important and critical aspect of modern phylogenetic and evolutionary analysis and so a considerable part of this volume addresses this important subject. The book is mainly written for students and researchers from evolutionary biology in search for methods to acquire data, but also from molecular biology who might be looking for information on how data are analyzed in an evolutionary context. To aid the user, information on web-located sites is included wherever possible. Approaches that will push the amount of information which systematics will gather in the
The fundamental principles of the scientific method are essential for enhancing perspective, increasing productivity, and stimulating innovation. These principles include deductive and inductive logic, probability, parsimony and hypothesis testing, as well as science's presuppositions, limitations, ethics and bold claims of rationality and truth. The examples and case studies drawn upon in this book span the physical, biological and social sciences; include applications in agriculture, engineering and medicine; and also explore science's interrelationships with disciplines in the humanities such as philosophy and law. Informed by position papers on science from the American Association for the Advancement of Science, National Academy of Sciences and National Science Foundation, this book aligns with a distinctively mainstream vision of science. It is an ideal resource for anyone undertaking a systematic study of scientific method for the first time, from undergraduates to professionals in both the sciences and the humanities.
An introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics. This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website.