Night Science: The Creative Side of Scientific Research

Where do ideas come from? This is an important question to Itai Yanai, CDS affiliated professor and the Director at the Institute for Computational Medicine at NYU Langone Health. When many people think of science, creativity may not be the first thing that comes to mind. The Professor of Biochemistry and Molecular Pharmacology holds a different perspective, one in which he has started a new podcast, Night Science, to explore. What is night science? As Itai and his podcast co-host and colleague Martin Lercher, describe in their paper by the same name, night science — a term and concept originally coined by French biologist François Jacob — refers to a process where scientists look at “the unstructured realm of possible hypotheses, of ideas not yet fully fleshed out.”

Figure 1 from “Night Science”: “The popping-out model of day science and night science. Day thinking proceeds in logical steps, and thus only ideas that are closely related to the current hypothesis can realistically be reached (symbolized by the isolated valleys in the lower part of the picture). But one can pop out to the much more open night science world, where leaps among ideas are made possible by intuition, associative thinking, unexplained observations, and loosely applied principles from other fields. When a new idea has been generated, one can pop back into the day below and test it efficiently using day science methods.”(1)

In each episode of their podcast, they discuss the creative side of science with a different scientist. Most recently, they interviewed Professor Yana Bromberg of the Department of Biochemistry and Microbiology at Rutgers, who is also a recipient of the CAREER award from the National Science Foundation. One aspect Yana focuses on in her work is teaching computers how to speak the “functional language of biological sequences”. The conversation in this episode, “Yana Bromberg on getting creative with machine learning”, centers mostly on the creativity that machine learning has to offer. Yana explains that her incentive, early in her career as a grad student, was to investigate if and how machine learning could be used to predict the effects of human genome variants.

As Night Science evolves as a podcast and project, it will hopefully bring more awareness and appreciation of creativity and night science within the scientific community.

To listen to the podcast, please visit the Night Science podcast website. To read the “Night Science” paper in its entirety, please visit the project’s BMC page. To learn more about the general Night Science project, please visit the Night Science website.

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By Ashley C. McDonald

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