703: How Data Happened: A History — with Columbia Prof. Chris Wiggins

Transformation

Chris Wiggins discusses the transformative impact of data science on biological research, starting from the early 1990s. He recalls how the sequencing of the first freely living organism's genome in 1995 marked a pivotal moment, leading to the sequencing of more complex organisms and eventually humans. This shift necessitated collaboration between biologists and data scientists to make sense of the vast amounts of data generated 1.

By the time I finished my PhD, the attitude among real biologists about data had completely flipped. And biologists were publishing papers like, we really need to collaborate with people who know how to make sense of data.

--- Chris Wiggins

Wiggins emphasizes the importance of effective models and machine learning methods in understanding biological data, highlighting the interdisciplinary nature of modern biological research.

   

Applications

Wiggins provides specific examples of how data science techniques are applied in biological research. He mentions his own journey into computational biology, driven by the need to distinguish valuable methods from ineffective ones. Over the past two decades, his research has focused on applying machine learning to biological sequence data, image data, and network data 2.

I felt like the only way to really know what was good and what was bad was to get in the ring and to try to start using these methods and answering biological questions.

--- Chris Wiggins

Wiggins collaborates closely with biologists to reframe their questions as machine learning tasks, providing interpretable insights that advance the field.