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Logic and Critical Thinking in the Biomedical Sciences

Volume I: Deductions Based Upon Simple Observations

  • 1st Edition - July 3, 2020
  • Latest edition
  • Author: Jules J. Berman
  • Language: English

Science is not a collection of facts. Science is the process by which we draw inferences from facts. Volume I of Logic and Critical Thinking in the Biomedical Sciences invite… Read more

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Description

Science is not a collection of facts. Science is the process by which we draw inferences from facts. Volume I of Logic and Critical Thinking in the Biomedical Sciences invites readers to linger over a collection of common observations to see what inferences can be drawn, when one applies a bit of deductive logic. If we just think about what we observe, it is often possible to discover profound biomedical insights.Volumes 1 and 2 of Logic and Critical Thinking in the Biomedical Sciences are written for biomedical scientists and college-level students engaged in any of the life sciences, including bioinformatics and related data sciences.

Key features

  • Provides a strong introduction to deductive methods that can be directly applied to the biomedical sciences
  • Using hundreds of examples, shows how creative scientists draw important inferences from observations that are often ignored by their peers
  • Discusses complex biological and medical concepts in a relaxed manner, intended to focus the reader’s attention on the deductive process, without dwelling excessively on details

Readership

Bioinformaticians; biostatisticians; graduate students; medical students. Members of biomedical field in general who deal with data

Table of contents

1. Introduction to biomedical logic Section 1.1. What is reasoning? Section 1.2. What is proof? Section 1.3. Fallacies Section 1.4. Can several weak arguments substitute for one strong argument?

2. Drawing inferences from photographs Section 2.1. Thinking about what we see Section 2.2. Looking at nuclei Section 2.3. Deducing that the chloroplasts in plant cells are captured cyanobacteria Section 2.4. Phylogenetic advances manifest themselves in the embryo Section 2.5. All eutherian cell types are equivalent among classes of speciesSection 2.6. Length of gestation in eutherian animals Section 2.7. Inferring that there are many more than 200 cell typesSection 2.8. What we learn from looking at red blood cellsSection 2.9. What we learn from inclusion bodies

3. Inferences drawn from organismal development Section 3.1. Desmosomes, the essence of animals Section 3.2. Ear ossicles missing from reptiles Section 3.3. The wisdom of teeth Section 3.4. The development of bones Section 3.5. Unnecessary cerebellum Section 3.6. Mammalian hair and the origin of basal cell carcinoma Section 3.7. Inferences drawn from the shape of snake heads Section 3.8. Depth of penetration of ultraviolet light Section 3.9. Evolution is often a one-way road

4. Inferences drawn from temporal sequences Section 4.1. Paradoxes of creation Section 4.2. A logical approach to bootstrapping paradoxes Section 4.3. Inferences drawn from the sequence of clinical events preceding death Section 4.4. When was aging invented? Section 4.5. When does aging begin? Section 4.6. Old age does not cause cancer Section 4.7. What can we infer when we know the time at which a mutation occurred?

5. Finding relationships among biological entities Section 5.1. Defining relationships and similarities Section 5.2. Ancestral genes Section 5.3. The significance of gene sequence conservation Section 5.4. Unexpected gene conservation Section 5.5. Relationships between human diseases and orthodiseases Section 5.6. Inferring the relationships between genetic diseases and their phenocopiesSection 5.7. The logic of treating disease pathways, not disease genes

6. Drawing inferences from classifications and ontologies Section 6.1. What is a classification? Section 6.2. Ontologies Section 6.3. Some paradoxes of classifications Section 6.4. The classification of living organisms and the meaning of “species”Section 6.5. Speciation is the primary driver of evolution Section 6.6. Classifications allow us to discover class-specific treatments of diseases

7. Biomedical advances achieved by reducing class noise Section 7.1. Significance of class noise Section 7.2. Why fungi are definitely not plants? Section 7.3. Naegleria fowleri is not an amoeba Section 7.4. Clinical trials for staged cancers Section 7.5. Psychiatric illnesses Section 7.6. Cures for the most common and chronic diseases Section 7.7. The mistake of overclassifying in an effort to avoid class blending

8. How a little logic could have corrected long-held misbeliefs Section 8.1. We should have known better Section 8.2. An embryo is not a miniature baby Section 8.3. The genome is a recipe book, not a blueprint Section 8.4. Why our genome is full of junk Section 8.5. Bacteria live in our stomachs Section 8.6. We can abandon Koch’s postulates Section 8.7. Diseases arise through a sequence of events that occur over time Section 8.8. The egalitarian nature of logical analysis

Product details

  • Edition: 1
  • Latest edition
  • Published: July 3, 2020
  • Language: English

About the author

JB

Jules J. Berman

Jules J. Berman, Ph.D., M.D. holds degrees from MIT, Temple University, and the University of Miami. He served as Chief of Anatomic Pathology, Surgical Pathology, and Cytopathology at the Veterans Administration Medical Center in Baltimore, Maryland, with joint appointments at the University of Maryland Medical Center and at the Johns Hopkins Medical Institutions. He later served at the US National Cancer Institute as a medical officer and as program director for pathology informatics in the Cancer Diagnosis Program. Dr. Berman is a past president of the Association for Pathology Informatics and the 2011 recipient of the association’s Lifetime Achievement Award.Jules J. Berman, Ph.D., M.D. holds degrees from MIT, Temple University, and the University of Miami. He served as Chief of Anatomic Pathology, Surgical Pathology, and Cytopathology at the Veterans Administration Medical Center in Baltimore, Maryland, with joint appointments at the University of Maryland Medical Center and at the Johns Hopkins Medical Institutions. He later served at the US National Cancer Institute as a medical officer and as program director for pathology informatics in the Cancer Diagnosis Program. Dr. Berman is a past president of the Association for Pathology Informatics and the 2011 recipient of the association’s Lifetime Achievement Award. He has first-authored more than 100 journal articles and has written 18 science books. His most recent titles, published by Elsevier, include:

-Taxonomic Guide to Infectious Diseases: Understanding the Biologic Classes of Pathogenic Organisms, 1st edition (2012) -Principles of Big Data: Preparing, Sharing, and Analyzing Complex Information (2013) -Rare Diseases and Orphan Drugs: Keys to Understanding and Treating the Common Diseases (2014) -Repurposing Legacy Data: Innovative Case Studies (2015) -Data Simplification: Taming Information with Open Source Tools (2016) -Precision Medicine and the Reinvention of Human Disease (2018) -Principles and Practice of Big Data: Preparing, Sharing, and Analyzing Complex Information, Second Edition (2018) -Taxonomic Guide to Infectious Diseases: Understanding the Biologic Classes of Pathogenic Organisms, 2nd edition (2019)

Affiliations and expertise
Author with expertise in informatics, computer programming, and cancer biology

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