I attended the Institute for System Biology Future of Health Symposium 2019. If I use the scale of WUKID (Wisdom Understanding Knowledge Information and Data) I barely functioned somewhere between the data and information level.  I heard the words and I saw the stunning array of data visualizations, but most of the content flew over my head.  I was in deep “trying to learn” mode.

Professor Phil Greenberg started us off with a talk on “Utilizing Synthetic Biology and High-Dimensional Probing to Address Therapeutic Obstacles and Empower Engineered T Cells with the Capacity to Eradicate Tumors.”  I was lost at the title.

Professor Phil Greenberg

As the data visualization slides started coming fast and furious, I was excited about the range of visualizations I encountered.  As visual analytics are a core part of my professional interests and research, I focused on what I could understand and let the moledular biology, systems biology, and immunotherapy deep dive wash over me.

I was enthralled with what was termed the Classic Disney gene clustering diagram.  I had never heard of this style.  A quick internet lookup didn’t tell me anything about the form of the diagram.  My hypothesis is that the colored gene cluster on the left looks like a colored map of the different “lands” at Disney World.

Classic Disney Gene Cluster

After spending eight hours listening to intellectually and visually engaging presentations on immunotherapies I came away excited about two areas of scientific research progress:

• Researchers are much farther along with precision medicine and cancer treatments for N=1 patient populations than I was aware of
• Data visualizations are an important part of communicating the scientific research in molecular biology, systems biology and medical research

For twenty years I have tilted at the windmill of business WUKID to move from “death by powerpoint” presentations that are bullet point after bullet point to powerful data visualizations and even better visual analytics.  Business is stuck in simplistic data visualization that begins and ends with pie charts and bar charts.

As my career journey follows a path back to health care, I am delighted to see a research discipline like systems biology and 21st century medical research so dependent on high quality data visualizations.

Now I have two more areas of learning to dive into:

• Systems biology and its relationship to P4 Medicine (Predictive, Preventive, Personalized, and Participatory)
• How systems biology as a discipline came to use data visualization and visual analytics so pervasively?