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  <titleInfo>
    <title>Experimental design for biologists</title>
  </titleInfo>
  <name type="personal">
    <namePart>Glass, David J.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="text">Cold Spring Harbor, New York</placeTerm>
    </place>
    <publisher>Cold Spring Harbor Laboratory Press</publisher>
    <dateIssued>2014</dateIssued>
    <edition>2a edition </edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">print</form>
    <extent>viii, 289 Pages illustrations</extent>
  </physicalDescription>
  <tableOfContents>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.</tableOfContents>
  <note type="statement of responsibility">David J. Glass, Novartis Institutes for Biomedical Research.</note>
  <note>Incluye referencias bibliográficas e índices</note>
  <subject authority="">
    <topic>Biología</topic>
    <topic>Modelos matemáticos</topic>
  </subject>
  <subject authority="">
    <topic>Diseño experimental</topic>
    <topic>Investigacion cientifica</topic>
  </subject>
  <classification authority="nlm">QH 323.5 </classification>
  <identifier type="isbn">9781621820413 (hardback)</identifier>
  <identifier type="isbn">1621820416 (hardback)</identifier>
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    <recordCreationDate encoding="marc">240219</recordCreationDate>
    <recordChangeDate encoding="iso8601">20240219111740.0</recordChangeDate>
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