Andrew Severin

Andrew Severin

His PhD was in Biophysics/NMR spectroscopy. He did a Bioinformatics Postdoc in Soybean genetics and now runs the Genome Informatics Facility at Iowa State University. He is passionate about evolution and the science behind the genome. There is so much we don't know about how the elements in a genome interact to create the fine balance of gene expression, modification and 3D structure that create the dynamic range of phenotypes we observe. As sequencing technology continues to improve and the cost continues to decrease, we will be able to ask more complex questions that increase our understanding via comparative and translational genomics.

Introduction to Experimental Design

Bioinformatics and data analysis starts with a good experimental design. In this section we will explore the aspects of experimental design that are important to a successful bioinformatic data analysis.

Learning Objective

Upon completion of this section on experimental design the learner will be able to:

  • Assess the assumptions and limitations of the biological domain and the sequencing technology as it relates to a biology question of interest
  • Evaluate which sequencing technology will provide the best results for a given project
  • Determine the limitations that result from reducing the amount of data collected in order to fit within a given budget.

Index

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