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Experimental Design for Biologists

Handbook / Manual

By: David J Glass (Author)

Cold Spring Harbor Laboratory Press

Hardback | Sep 2014 | Edition: 2 | #216338 | ISBN-13: 9781621820413
Availability: Usually dispatched within 6 days Details
NHBS Price: £23.99 $30/€29 approx

About this book

The effective design and analysis of experiments in biology are critical to success, yet graduate students in biological and medical sciences typically receive very little formal training in these steps. With feedback from readers of the first edition, colleagues, and students taking the very popular experimental design courses taught by the author, this second edition of Experimental Design for Biologists retains the engaging writing style while organizing Experimental Design for Biologists around the four elements of experimental design: the framework, the system, the experiment, and the model. The approach has been tested in the classroom, where the author has taught numerous graduate students, MD/PhD students, and postdoctoral fellows. The goal of every scientist is to discover something new and with the aid of Experimental Design for Biologists, this task is made a little easier.

Experimental Design for Biologists explains how to establish the framework for an experimental project, how to set up all of the components of an experimental system, design experiments within that system, determine and use the correct set of controls, and formulate models to test the veracity and resiliency of the data. This thoroughly updated edition of Experimental Design for Biologists is an essential source of theory and practical guidance for designing a research plan.


Contents

Preface
 
Section One: Philosophy of Experimentation
1. Why You Need to Read a Little Philosophy First: The Philosophy of Science Governs the Practice of Science
2. Defining Scientific Research
3. Why Do Science? What Is Science For? The Need for Inductive Reasoning
4. The First Step to Engaging in Scientific Research: Establishing Your Framework
5. A Short History of Philosophy Relevant to Scientific Method: How We Got to Where We Are Today and the Problem of Induction
6. The Sky Is Red Hypothesis: Examining the Hypothesis-Falsification Framework
7. The Hypothesis as a Framework for Scientific Projects: Is Critical Rationalism Critical Enough?
8. Scientific Settings in Which a Hypothesis-Falsification Framework Is Not Feasible
9. The Question and the Model: Forming an Inductive Framework for Scientific Projects (by Getting to Carnegie Hall)
10. Advantages to the Question/Model-Building Inductive Framework
11. A Biological Example of the Question/Model-Building Framework
12. Some Concluding Remarks on the Philosophy of Experimentation: Warnings and Exhortations
 
Section Two: System Validation
13. The System
14. System Validation
15. Choice of a Model Organism or Technique: Validation Experiments
16. System Validation Requirements for Distinct Experimental Readouts
17. System Specificity: Specificity of Detection and Specificity of Perturbation
18. System Sensitivity: Minimizing Signal to Noise to Improve Sensitivity of Detection
19. System Stability
20. Determining Conditions to Measure Efficacy
21. System Validation: Determining Conditions to Measure Safety
 
Section Three: The Experiment
22. Definition of the Experiment: The Framework for an Individual Experiment
23. The Negative Control: Distinct Types
24. The Requirement for the Positive Control
25. Method and Reagent Controls
26. Subject Controls
27. Assumption Controls
28. Experimentalist Controls: Establishing a Claim to an Objective Perspective
29. Biological Replicates, Technical Replicates, Experimental Repeats, Time Courses (Repeats over Time), and Dose Responses
30. Summary of the Components of the Individual Experiment
 
Section Four: The Model
31. Building the Model: Representations of the Experimental Data
32. Data Filtration
33. Model Induction: Asking Follow-Up Questions and Finishing the Project by Writing the Manuscript
34. A Short Synopsis
 
Section Five: Addendum
Designing the Experimental Project: A Biological Example
 
Index


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