John Reinitz, pioneering UChicago systems biologist and ‘fiercely independent thinker,’ 1958-2025

John Bertram Reinitz, a professor in the Departments of Statistics, Ecology and Evolution, Molecular Genetics & Cell Biology at the University of Chicago, who helped pioneer a data-driven approach to developmental biology, died Jan. 23 at the age of 66.

“John was a fiercely independent thinker. He went where the science brought him—without caring about the opinions of others—and attempted to crack problems that seemed insurmountable,” said Prof. Stefano Allesina, chair of the Department of Ecology and Evolution. “You could always rely on him for a dissenting voice, a quirky remark, or a different perspective.”

Reinitz helped usher in a systems approach to developmental biology that is now widely used in the field today. In the early 1990s, genetic research in developmental biology consisted almost entirely of qualitative, hypothesis-driven experiments; Reinitz developed an approach that relied instead on constructing an atlas—a comprehensive, spatially and temporally resolved, quantitative dataset—with no explicit hypothesis guiding the effort. 

Building spatiotemporal atlases has now become routine in developmental biology, a practice foreshadowed by Reinitz’s groundbreaking innovations. He also developed a model for predicting gene expression from DNA sequences.

An independent beginning

Reinitz began his research career as an independent PhD student at Yale University, where he devised a mathematical model of viral gene regulation that incorporated all the mechanisms known from experimental evidence at the time. This model revealed that the known mechanisms were insufficient to account for all the virus’s behaviors, which dismayed scientists who had heretofore regarded it as a solved problem. Sticking to his guns to contradict the conventional wisdom of a field, however, was a recurring theme in his career.

After a postdoctoral stint in Columbia University, Reinitz initiated the project that would evolve into the data-driven modeling approach that defined his career. 

Reinitz’s approach required many technologies that were yet to be invented. He raised a panel of antibodies to the segmentation proteins that he distributed to the Drosophila community for decades and is still in use today. He also developed bespoke optimization algorithms for fitting the models, devised protocols for quantitative fluorescence microscopy, and invented approaches for automated image segmentation that enabled the construction of the atlas at scale. 

His efforts bore fruit after he moved to Stony Brook University in 2000. The spatiotemporal atlas revealed that gene expression domains were not static as assumed but shifted along the axis of the embryo as development progressed. 

With the aid of the connectionist model, Reinitz and his lab showed that this motion was driven by asymmetric gene regulation, proving that embryos do not passively receive information from the mother, but actively self-organize to determine their body plan.

Next, Reinitz leveraged advances in bioinformatics to develop a model for predicting gene expression from DNA sequences that has been highly successful in explaining gene regulation, including that of evolutionarily diverged sequences. 

What Reinitz pioneered at a small scale thirty years ago is now practiced across disciplines in a large-scale manner. While there wasn’t a name for such work when Reinitz started, data-driven gene network inference and modeling came to be known as “systems biology” by the early 2000s.

Reinitz moved to the University of Chicago in 2011, with appointments in both the Biological and Physical Sciences Divisions.

“John personified a major tenet of our department—that statistics flourishes when engaged with serious scientific problems and vice versa,” said Stephen Stigler, Ernest DeWitt Burton Distinguished Service Professor Emeritus of Statistics. “John brought statistical modeling into his laboratory work, and he enthusiastically brought his insights from the DNA laboratory into his teaching of statistics.”

Having established the modeling approaches in developmental biology, Reinitz applied them to other areas, particularly evolutionary biology, stochastic gene regulation, and machine learning. He remained active until the very end; his latest efforts involved using cutting-edge, single-molecule techniques to understand the role and control of stochastic fluctuations in gene regulation.

A long, strange trip

Reinitz had a truly engaging and colorful personality with a razor-sharp wit; a comment in his code read: “I could explain how this works, but then I’d have to kill you.” He prized straight talk and an open exchange of ideas, and it was hard for his trainees to not be infected by his independent and rebellious bulldog streak, his students said. 

A lifelong Grateful Dead and Phish fan, he dedicated the source code of the connectionist model to Jerry Garcia after the musician’s death.

Science fiction and fantasy, especially the works of J.R.R. Tolkien, were another passion. Blessed with a rapacious memory, colleagues said, it was rare to have a conversation in which he did not quote verbatim either song lyrics or some snippet from sci-fi literature. He loved to travel, especially internationally, and developed collaborations across the globe, including Russia, France and Brazil.

Reinitz is survived by his wife, Dr. Ilene Reinitz, and daughter Julia Reinitz.

—Adapted from a longer obituary provided by Johannes Jaeger, Associate Faculty at the Complexity Science Hub in Vienna, Austria, and Manu, Associate Professor in the Department of Biology at the University of North Dakota, two former students of John Reinitz.