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Experemental Dsign for Biologists
"Experimental Design for Biologists is a unique and successful handbook on the theory and practice of effective design of scientific experiments, based on a well-received course by the author. This second edition is entirely reorganized, rewritten, and includes new material and figures. The...
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| Format: | Printed Book |
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New York
Cold Spring Harbor Laboratory Press
2014
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| Edition: | 2nd ed. |
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Table of Contents:
- Why you need to read a little philosophy first: the philosophy of science governs the practice of science
- Defining scientific research
- Why do science? What is science for? The need for inductive reasoning
- The first step to engaging in scientific research: establishing your framework
- A short history of philosophy relevant to scientific method: how we got to where we are today and the problem of induction
- The sky is red hypothesis: examining the hypothesis-falsification framework
- The hypothesis as a framework for scientific projects: is critical rationalism critical enough?
- Scientific settings in which a hypothesis-falsification framework is not feasible
- The question and the model: forming an inductive framework for scientific projects (by getting to Carnegie Hall)
- Advantages to the question/model-building inductive framework
- A biological example of the question/model-building framework
- Some concluding remarks on the philosophy of experimentation: warnings and exhortations
- The system
- System validation
- Choice of a model organism or technique: validation experiments
- System validation requirements for distinct experimental readouts
- System specificity: specificity of detection and specificity of perturbation
- System sensitivity: minimizing signal to noise to improve sensitivity of detection
- System stability
- Determining conditions to measure efficacy
- System validation: determining conditions to measure safety
- Definition of the experiment: the framework for an individual experiment
- The negative control: distinct types
- The requirement for the positive control
- Method and reagent controls
- Subject controls
- Assumption controls
- Experimentalist controls: establishing a claim to an objective perspective
- Biological replicates, technical replicates, experimental repeats, time courses (repeats over time), and dose responses
- Summary of the components of the individual experiment
- Building the model: representations of the experimental data
- Data filtration
- Model induction: asking follow-up questions and finishing the project by writing the manuscript
- A short synopsis
- Designing the experimental project: a biological example.