Despite the transformation in biological practice and theory brought about by discoveries in molecular biology, until recently philosophy of biology continued to focus on evolutionary biology. When the Human Genome Project got underway in the late 1980s and early 1990s, philosophers of biology—unlike historians and social scientists—had little to add to the debate. In this landmark collection of essays, Sahotra Sarkar broadens the scope of current discussions of the philosophy of biology, viewing molecular biology as a unifying perspective on life that complements that of evolutionary biology. His focus is on molecular biology, but the overriding question behind these papers is what molecular biology contributes to all traditional areas of biological research.Molecular biology—described with some foresight in a 1938 Rockefeller Foundation report as a branch of science in which "delicate modern techniques are being used to investigate ever more minute details"—and its modeling strategies apparently argue in favor of physical reductionism. Sarkar's first three chapters explore reductionism—defending it, but cautioning that reduction to molecular interactions is not necessarily a reduction to genetics (and does not support the claims of either heriditarianism or environmentalism). The next sections of the book discuss function, exploring how functional explanations pose a problem for reductionism; the informational interpretation of biology and how it interacts with reductionism; and the tension between the unifying framework of molecular biology and the received framework of evolutionary theory. The concluding chapter is an essay in the emerging field of developmental evolution, exploring what molecular biology may contribute to the transformation of evolutionary theory as evolutionary theory takes into account morphogenetic development.

Despite the transformation in biological practice and theory brought about by discoveries in molecular biology, until recently philosophy of biology continued to focus on evolutionary biology. When the Human Genome Project got underway in the late 1980s and early 1990s, philosophers of biology -- unlike historians and social scientists -- had little to add to the debate. In this landmark collection of essays, Sahotra Sarkar broadens the scope of current discussions of the philosophy of biology, viewing molecular biology as a unifying perspective on life that complements that of evolutionary biology. His focus is on molecular biology, but the overriding question behind these papers is what molecular biology contributes to all traditional areas of biological research.Molecular biology—described with some foresight in a 1938 Rockefeller Foundation report as a branch of science in which "delicate modern techniques are being used to investigate ever more minute details"—and its modeling strategies apparently argue in favor of physical reductionism. Sarkar's first three chapters explore reductionism—defending it, but cautioning that reduction to molecular interactions is not necessarily a reduction to genetics (and does not support the claims of either heriditarianism or environmentalism). The next sections of the book discuss function, exploring how functional explanations pose a problem for reductionism; the informational interpretation of biology and how it interacts with reductionism; and the tension between the unifying framework of molecular biology and the received framework of evolutionary theory. The concluding chapter is an essay in the emerging field of developmental evolution, exploring what molecular biology may contribute to the transformation of evolutionary theory as evolutionary theory takes into account morphogenetic development.

Written by experienced experts in molecular modeling, this books describes the basics to the extent that is necessary if one wants to be able to reliably judge the results from molecular modeling calculations. Its main objective is the description of the various pitfalls to be avoided. Without unnecessary overhead it leads the reader from simple calculations on small molecules to the modeling of proteins and other relevant biomolecules. A textbook for beginners as well as an invaluable reference for all those dealing with molecular modeling in their daily work!

The question of "what is thought" has intrigued society for ages, yet it is still a puzzle how the human brain can produce a myriad of thoughts and can store seemingly endless memories. All we know is that sensations received from the outside world imprint some sort of molecular signatures in neurons – or perhaps synapses – for future retrieval. What are these molecular signatures, and how are they made? How are thoughts generated and stored in neurons? The Biology of Thought explores these issues and proposes a new molecular model that sheds light on the basis of human thought. Step-by-step it describes a new hypothesis for how thought is produced at the micro-level in the brain – right at the neuron. Despite its many advances, the neurobiology field lacks a comprehensive explanation of the fundamental aspects of thought generation at the neuron level, and its relation to intelligence and memory. Derived from existing research in the field, this book attempts to lay biological foundations for this phenomenon through a novel mechanism termed the "Molecular-Grid Model" that may explain how biological electrochemical events occurring at the neuron interact to generate thoughts. The proposed molecular model is a testable hypothesis that hopes to change the way we understand critical brain function, and provides a starting point for major advances in this field that will be of interest to neuroscientists the world over. - Written to provide a comprehensive coverage of the electro-chemical events that occur at the neuron and how they interact to generate thought - Provides physiology-based chapters (functional anatomy, neuron physiology, memory) and the molecular mechanisms that may shape thought - Contains a thorough description of the process by which neurons convert external stimuli to primary thoughts

Studies of evolution at the molecular level have experienced phenomenal growth in the last few decades, due to rapid accumulation of genetic sequence data, improved computer hardware and software, and the development of sophisticated analytical methods. The flood of genomic data has generated an acute need for powerful statistical methods and efficient computational algorithms to enable their effective analysis and interpretation. Molecular Evolution: a statistical approach presents and explains modern statistical methods and computational algorithms for the comparative analysis of genetic sequence data in the fields of molecular evolution, molecular phylogenetics, statistical phylogeography, and comparative genomics. Written by an expert in the field, the book emphasizes conceptual understanding rather than mathematical proofs. The text is enlivened with numerous examples of real data analysis and numerical calculations to illustrate the theory, in addition to the working problems at the end of each chapter. The coverage of maximum likelihood and Bayesian methods are in particular up-to-date, comprehensive, and authoritative. This advanced textbook is aimed at graduate level students and professional researchers (both empiricists and theoreticians) in the fields of bioinformatics and computational biology, statistical genomics, evolutionary biology, molecular systematics, and population genetics. It will also be of relevance and use to a wider audience of applied statisticians, mathematicians, and computer scientists working in computational biology.

Very broad overview of the field intended for an interdisciplinary audience; Lively discussion of current challenges written in a colloquial style; Author is a rising star in this discipline; Suitably accessible for beginners and suitably rigorous for experts; Features extensive four-color illustrations; Appendices featuring homework assignments and reading lists complement the material in the main text

A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems. There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.