Main description:

Honorable mention Biomedicine and Neuroscience,2011 Prose Awards

An examination of how the cell should be described in orderto effectively process biological data

"The fruitful pursuit of biological knowledge requires one totake Einstein′s admonition [on science without epistemology] as apractical demand for scientific research, to recognize Waddington′scharacterization of the subject matter of biology, and to embraceWiener′s conception of the form of biological knowledge in responseto its subject matter. It is from this vantage point that weconsider the epistemology of the cell."
from the Preface

In the era of high biological data throughput, biomedicalengineers need a more systematic knowledge of the cell in order toperform more effective data handling. Epistemology of theCell is the first authored book to break down this knowledge.This text examines the place of biological knowledge within theframework of science as a whole and addresses issues focused on thespecific nature of biology, how biology is studied, and howbiological knowledge is translated into applications, in particularwith regard to medicine.

The book opens with a general discussion of the historicaldevelopment of human understanding of scientific knowledge, thescientific method, and the manner in which scientific knowledge isrepresented in mathematics. The narrative then gets specific forbiology, focusing on knowledge of the cell, the basic unit of life.The salient point is the analogy between a systems–based analysisof factory regulation and the regulation of the cell. Each chapterrepresents a key topic of current interest, including:

• Causality and randomness




• Translational science




• Stochastic validation: classification




• Stochastic validation: networks




• Model–based experimentation in biology

Epistemology of the Cell is written for biomedicalresearchers whose interests include bioinformatics, biologicalmodeling, biostatistics, and biological signal processing.

Back cover:

Honorable mention Biomedicine and Neuroscience,2011 Prose Awards

An examination of how the cell should be described in orderto effectively process biological data

"The fruitful pursuit of biological knowledge requires one totake Einstein′s admonition [on science without epistemology] as apractical demand for scientific research, to recognize Waddington′scharacterization of the subject matter of biology, and to embraceWiener′s conception of the form of biological knowledge in responseto its subject matter. It is from this vantage point that weconsider the epistemology of the cell."
from the Preface

In the era of high biological data throughput, biomedicalengineers need a more systematic knowledge of the cell in order toperform more effective data handling. Epistemology of theCell is the first authored book to break down this knowledge.This text examines the place of biological knowledge within theframework of science as a whole and addresses issues focused on thespecific nature of biology, how biology is studied, and howbiological knowledge is translated into applications, in particularwith regard to medicine.

The book opens with a general discussion of the historicaldevelopment of human understanding of scientific knowledge, thescientific method, and the manner in which scientific knowledge isrepresented in mathematics. The narrative then gets specific forbiology, focusing on knowledge of the cell, the basic unit of life.The salient point is the analogy between a systems–based analysisof factory regulation and the regulation of the cell. Each chapterrepresents a key topic of current interest, including:

• Causality and randomness




• Translational science




• Stochastic validation: classification




• Stochastic validation: networks




• Model–based experimentation in biology

Epistemology of the Cell is written for biomedicalresearchers whose interests include bioinformatics, biologicalmodeling, biostatistics, and biological signal processing.

Contents:

Preface ix

Acknowledgments xi

1. Science and Knowledge 1

2. Causality and the Three Pillars of Aristotelian Science11

3. Scientific Knowledge 35

4. Cells and Factories 59

5. Translational Science 85

6. Stochastic Validation: Classifi ers 97

7. Stochastic Validation: Networks 129

8. Sola Fides 147

9. Model–based Experimentation in Biology 169

References 189

Index 197

IEEE Press Series on Biomedical Engineering 203