William Bialek

About

William Bialek is a Professor of Physics and a co-Director at the Center for the Physics of Biological Function (CPBF), an NSF Physics Frontier Center. He is also a Lewis-Sigler Institute faculty member at Princeton University and holds the position of Visiting Professor of Physics at The Graduate Center, CUNY. His research focuses on the physics of biological function, contributing to the understanding of biological systems through the lens of physics. Bialek's work involves exploring the fundamental principles underlying biological processes, integrating concepts from physics to analyze complex biological phenomena.

Research topics

• Computer science
• Statistical physics
• Physics
• Artificial intelligence
• Mathematics

Selected publications

• Long Timescales, Individual Differences, and Scale Invariance in Animal Behavior

  Physical Review Letters · 2024-01-22 · 20 citations

  articleOpen access1st authorCorresponding

  The explosion of data on animal behavior in more natural contexts highlights the fact that these behaviors exhibit correlations across many timescales. However, there are major challenges in analyzing these data: records of behavior in single animals have fewer independent samples than one might expect. In pooling data from multiple animals, individual differences can mimic long-ranged temporal correlations; conversely, long-ranged correlations can lead to an overestimate of individual differenc…

  PublisherOA PDFDOI

• Deriving a genetic regulatory network from an optimization principle

  Proceedings of the National Academy of Sciences · 2025-01-03 · 18 citations

  articleOpen accessCorresponding

  Many biological systems operate near the physical limits to their performance, suggesting that aspects of their behavior and underlying mechanisms could be derived from optimization principles. However, such principles have often been applied only in simplified models. Here, we explore a detailed mechanistic model of the gap gene network in the Drosophila embryo, optimizing its 50+ parameters to maximize the information that gene expression levels provide about nuclear positions. This optimizati…

  PublisherDOI

• Finding the Last Bits of Positional Information

  PRX Life · 2024-03-26 · 17 citations

  articleOpen accessSenior author

  In a developing embryo, information about the position of cells is encoded in the concentrations of morphogen molecules. In the fruit fly, the local concentrations of just a handful of proteins encoded by the gap genes are sufficient to specify position with a precision comparable to the spacing between cells along the anterior-posterior axis. This matches the precision of downstream events such as the striped patterns of expression in the pair-rule genes, but is not quite sufficient to define u…

  PublisherOA PDFDOI

• Scale invariance in early embryonic development

  Proceedings of the National Academy of Sciences · 2024-11-08 · 14 citations

  articleOpen access

  The expression of a few key genes determines the body plan of the fruit fly. We show that the spatial expression patterns for several of these genes scale precisely with embryo size. Discrete positional markers such as the peaks in striped patterns or the boundaries of expression domains have positions along the embryo's major axis proportional to embryo length, accurate to within 1%. Further, the information (in bits) that graded patterns of expression provide about a cell's position can be dec…

  PublisherOA PDFDOI

• Exact minimax entropy models of large-scale neuronal activity

  Physical review. E · 2025-05-19 · 7 citations

  articleSenior author

  In the brain, fine-scale correlations combine to produce macroscopic patterns of activity. However, as experiments record from larger and larger populations, we approach a fundamental bottleneck: the number of correlations one would like to include in a model grows larger than the available data. In this undersampled regime, one must focus on a sparse subset of correlations; the optimal choice contains the maximum information about patterns of activity or, equivalently, minimizes the entropy of…

  PublisherDOI

Recent grants

• Mechanisms of neural circuit dynamics in working memory

  NIH · $3.1M · 2014–2018

• NIH Grant R01GM077599

  NIH · $1.2M · 2012

• A new paradigm for quantifying animal behavior in a model genetic system

  NIH · $1.6M · 2011–2016

Frequent coauthors

• Thomas Gregor

  Centre National de la Recherche Scientifique

  72 shared

• Eric Wieschaus

  Princeton University

  43 shared

• Gašper Tkačik

  Institute of Science and Technology Austria

  38 shared

• Christopher W. Lynn

  The Graduate Center, CUNY

  30 shared

• Rob R. de Ruyter van Steveninck

  Indiana University Bloomington

  28 shared

• David W. Tank

  Princeton University

  26 shared

• Mariela D. Petkova

  Harvard University

  23 shared

• Olivier Marre

  Sorbonne Université

  23 shared

Labs

• Center for the Physics of Biological FunctionPI

Education

• Postdoctoral, Theoretical Physics

  University of California, Santa Barbara

  1986

• Postdoctoral, Physics

  Rijksuniversiteit Groningen

  1984

• PhD, Biophysics

  University of California, Berkeley

  1983

• AB, Biophysics

  University of California, Berkeley

  1979

Similar researchers at Princeton University

• Robert Austinh-95