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Course philosophy

Clear and efficient communication is a crucial—and often neglected—aspect of science. Intentional or unintentional miscommunication of research and data can result in adverse consequences; some examples include a flawed Challenger launch decision, inconsistent usage of units with the Mars Climate Orbiter, poor communication between experts and scientists with the public during the COVID-19 pandemic, and rampant misinformation. Lectures, assignments, and activities for this course are designed to teach you the tools to communicate effectively and comprehend scientific literature in computational biology.

What makes good written or visual communication? The answer is highly subjective. I argue that there is no "correct way" to communicate, and it depends on both the material's producer and consumer. Some things could make papers or presentations incomprehensible, but everything else that turns "acceptable" into "excellent" is a matter of taste.

Furthermore, it's essential to recognize that computational biology is a rapidly evolving landscape. To keep up-to-date, we must ensure our working knowledge is broad enough to comprehend and incorporate advancements quickly. We'll look at many different topics in computational biology, exploring its complex details and the changes it leads to.

My principal goals for this course are to equip you with the tools to

  • Navigate and understand the various subfields of computational biology;
  • Organize, draft, revise, and finish preparing writings and presentations;
  • Recognize what aspects hamper written (e.g., grammar, organization, formatting) and visual (e.g., color, design, pace) communication;
  • Discover your voice and style of communication;
  • Process and digest information from a variety of different scientific sources.