ABI OMICSS Guide 2021
  • Welcome
  • Week 1
    • Molecular Biology
      • Introduction to Biology
      • Macromolecules
      • DNA & RNA
      • Cell Division
    • Command-Line
      • Connecting to the Server
      • The Linux Command-Line For Beginners
      • The Bash Terminal
    • R Programming
      • Getting Started
      • The Basics
      • Data Types
    • Week 1 Exam
  • Week 2
    • Molecular Biology
      • DNA Proofreading And Repair
      • Telomeres and Telomerase
      • Genes
      • The One Gene, One Enzyme Hypothesis
      • Transcription
      • Translation
    • R Programming
      • Data Types (continuation)
      • Reading Data
      • Subsetting
      • Control Structures
      • Functions
      • Scoping Rules
    • Week 2 Exam
  • Week 3
    • Molecular Biology
      • tRNA and Ribosomes
      • Stages of Translation & Protein Targeting
      • Heredity
      • Probabilities In Genetics
    • R Programming
      • Loop Functions
      • Base Graphics
    • Statistics and R
      • The Basics
    • Week 3 Exam
  • Week 4
    • Molecular Biology
      • Interesting Cases of Genes
      • The Chromosomal Basis of Inheritance
      • Variation in Species
      • Phenotype plasticity
    • R Programming
      • Practice 2
      • Practice 3
    • Statistics and R
      • Random Variables and Probability Distributions
      • Central Limit Theorem
    • Week 4 Exam
  • Week 5
    • Statistics and R
      • Confidence Interval
      • Introduction to Inference
      • t-distribution and Comparing Means
      • Linear Models
    • Experimental Techniques
      • Polymerase Chain Reaction (PCR)
      • Gel Electrophoresis
      • Sanger Sequencing
      • NGS Sequencing
    • Week 5 Exam
  • Week 6
    • Statistics and R
      • Power
      • ANOVA
      • Covariance and Correlation
    • NGS
      • Basic Unix Commands
      • Sequences and Genomic Features
      • FastQC
      • Practice Exercises
    • Week 6 Exam
  • Week 7
    • Statistics and R
      • Monte Carlo Simulation
      • Exploratory Data Analysis
      • Linear Regression
    • NGS
      • BEDtools
      • Alignment and Sequence Variation
      • Integrated Genomics Viewer
    • Week 7 Exam
  • Week 8
    • NGS
      • Variant Calling With GATK
      • Practice 1
    • Week 8 Exam
  • Module Syllabi
  • Additional Resources
  • Conclusion
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  • What Are Experimental Techniques?
  • Why Should I Learn Experimental Techniques?
  • What Are the Learning Outcomes of This Week?

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  1. Week 5

Experimental Techniques

This module takes an estimated 1.5 hours to complete.

What Are Experimental Techniques?

Bioinformatics isn’t just about storing biological data in databases, it also concerns conducting experiments on that data. The Experimental Techniques module of this guide covers just that.

Why Should I Learn Experimental Techniques?

Finding a database entry you are interested in is database searching, but as soon as you want to draw a conclusion from your search – inferring homologs of a protein of interest for example – you are conducting an experiment and need to apply the same scientific methodologies in terms of controls, etc. that you would to an experiment in the laboratory. Therefore, it is important to be familiar with the experimental techniques used in Bioinformatics.

What Are the Learning Outcomes of This Week?

By the end of the week, you should:

  • Be familiar with the PCR theory

  • Have a solid understanding of gel electrophoresis

  • Know the basics of sanger sequencing

  • Have good knowledge of NGS sequencing

PreviousLinear ModelsNextPolymerase Chain Reaction (PCR)

Last updated 3 years ago

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