Epistemology of the Cell : A Systems Perspective on Biological Knowledge

by Dougherty, Edward R.; Bittner, Michael L.

• ISBN13: 9781118027790
• ISBN10: 1118027795
• Edition: 1st
• Format: Hardcover
• Copyright: 2011-08-30
• Publisher: Wiley-IEEE Press

Summary

This text examines the place of biological knowledge within the framework of science as a whole and addresses issues focused on the specific nature of biology, how biology is studied, and how biological knowledge is translated into applications, in particular, with regard to medicine. The book opens with a general discussion of the development of human understanding of scientific knowledge and method. The book gets specific focusing on knowledge of the cell, the basic unit of life. The salient point is the analogy between a systems-based analysis of factory regulation and the regulation of the cell. The book also includes information on translational science.

Author Biography

Edward R. Dougherty PhD is Director of the Genomic Signal Processing Laboratory at Texas A M University, where he holds the Robert M. Kennedy '26 Chair and is Professor in the Department of Electrical and Computer Engineering. He is also co-Director of the Computational Biology Division at the Translational Genomics Research Institute as well as Adjunct Professor in the Department of Bioinformatics and Computational Biology, M. D. Anderson Cancer Center at the University of Texas. Dr. Dougherty has published more than 300 peer-reviewed journal articles and "book chapters. Michael I. Bittner PhD is co-Director and Senior Investigator at the Computational Biology Division at the, Translational Genomics Research Institute. Previously, he was associate investigator in the Cancer Genetics Branch of the National Human Genome Research Institute at the National Institutes of Health. Dr. Bittner holds a dozen patents and has published more than 100 articles.

Table of Contents

Preface	p. ix
Acknowledgments	p. xi
Science and Knowledge	p. 1
Causality and the Three Pillars of Aristotelian Science	p. 11
Scientific Knowledge	p. 35
Cells and Factories	p. 59
Translational Science	p. 85
Stochastic Validation: Classifiers	p. 97
Stochastic Validation: Networks	p. 129
Sola Fides	p. 147
Model-based Experimentation in Biology	p. 169
References	p. 189
Index	p. 197
IEEE Press Series on Biomedical Engineering	p. 203
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