Menu Back to 014P-Data-Visualization-in-the-Lifesciences

Overview

Preregistration required and is an additional fee. Already registered? Log in to DIA's My Account>My Events.
Traditional approaches to medical product development rely on generating pages upon pages of analysis results to describe the safety and effectiveness of novel therapies. Study teams struggle to understand and communicate the story hidden within the data to their colleagues. First and foremost, with the high cost of conducting translational clinical research, it is common to collect as much data as possible on as many endpoints as possible. This phenomenon is further reinforced due to our limited understanding of biological mechanisms and pathways, including the potential genomic underpinnings of a disease or treatment response.

Ben Shneiderman stated that “the purpose of visualization is insight.” Therefore, the goal of this short course is to describe data visualization techniques to aid in the understanding and communication of results from applications in clinical trials and genomics research. Numerous practical illustrations and examples from the literature will be presented. To be accessible to a wide audience, this course will focus on principles and interpretation, and limit technical jargon.

Need approval in order to attend?

Download and fill out our Justification Letter to demonstrate to your supervisor why this is a must-attend event.



Enhance your experience and register for two or more short courses at the same time and receive $50 in savings.
Purchase must happen at same time. Discount will be reflected on the last page of the cart.


Upon completion of registration, participants will gain access to the following:

  • Live Event Access
  • Presentation Slides
  • Access to recorded sessions, on demand for 4 months post event


Download Registration Form

Registration Questions?

Send Email
1.888.257.6457


Return to

DIA 2021


Who should attend?

This short course is designed to be accessible to a wide audience, it will focus on principles, limit technical jargon, and interpret numerous examples of data visualization using data from the life sciences literature. The audience may include any individual interested in developing their skills for more efficient interpretation and communication of various aspects of study design and analysis.

Learning objectives

At the conclusion of this short course, participants should be able to:
  • Describe the transition from traditional methods of data analysis to visual approaches
  • Identify life science data using one or more data visualizations
  • Assess the strengths and limitations of various graphical techniques
  • Explain the “data story” of numerous clinical research, examples using data visualization techniques.