Nanofluidic devices, e.g. based on nanochannels or nanopores, are networks of fluid-filled structures on a chip with dimensions ~1-100 nm. These dimensions are on order of molecular length scales, giving rise to the ability to directly analyze, manipulate and confine single biomolecules. In this talk I will focus on two different…
Infectious disease-causing pathogens have plagued humanity since antiquity, and the COVID-19 pandemic has been a vivid reminder of this perpetual existential threat. Vaccination has saved more lives than any other medical procedure, and effective vaccines have helped control the COVID-19 pandemic. However, we do not have effective vaccines…
- Bill BialekAffiliationPrinceton University
- Josh ShaevitzAffiliationPrinceton University
The actomyosin cytoskeleton is a naturally occurring active gel found in virtually all mammalian cells. Its ability to contract allows cells to move, change shape, exert force, sense stiffness, and maintain constant tension. In order for the “hardware” of actomyosin gels to support such a diverse set of mechanical tasks, it is tightly coupled…
Aggregations are common in biological systems at a range of scales and may be driven by exogenous constraints such as environmental heterogeneity and resource availability or by “self-organizing” interactions among individuals. One mechanism leading to self-organized animal aggregations is captured by Hamilton’s “selfish herd” hypothesis, which…
Aggregations are common in biological systems at a range of scales and may be driven by exogenous constraints such as environmental heterogeneity and resource availability or by “self-organizing” interactions among individuals. One mechanism leading to self-organized animal aggregations is captured by Hamilton’s “selfish herd” hypothesis, which…
Super-resolution optical microscopy has become a powerful tool to study the nanoscale spatial distribution of molecules of interest in biological cells, tissues and other structures over the last years. Imaging these distributions in the context of other molecules or the general structural context is, however, still challenging. I will present…
To understand computation in the brain, one needs to understand the input-output relationships for neural circuits and the anatomical and functional properties of individual neurons therein. Optical microscopy has emerged as an ideal tool in this quest, as it is capable of recording the activity of…
The urgency to probe biological dynamics is impeded by a major challenge: the large dynamic range of biological processes—interactions of molecules within milliseconds can lead to changes across the whole-organism over days to years. It calls for measurements with both high spatiotemporal resolution and large-scale long-term coverage. However,…
Animal genomes are folded into loops and topologically associating domains (TADs) by CTCF and loop extruding cohesins. These loops and domains are thought to play critical roles in regulating gene expression by regulating long-range enhancer-promoter interactions. But whether CTCF/cohesin loops are stable or dynamic structures was…
In the event of metastatic disease, emergence of a lesion can occur at varying intervals from diagnosis and in some cases following successful treatment of the primary tumor. Genetic factors that drive metastatic progression have been identified, such as those involved in cell adhesion, signaling, extravasation and metabolism. However,…
We are interested in how physics at the colloidal scale instantiate life in biological cells. While principles from physics have driven recent paradigm shifts in how collective biomolecular behaviors orchestrate life, many mechanistic aspects of e.g. transcription, translation, and condensation remain mysterious because…
My lab studies the brains of larval fruit flies as models of neural computation. We are interested in the rules by which the larval brain transforms sensory input into motor output to navigate an uncertain environment, how the larva’s brain changes these rules as it learns new information, and how these rules and changes are encoded in the…
Measurement of natural systems typically involves perturbation and interpretation. In this talk, I will discuss the implications of measurement in the context of RNA in gene expression in human cells. I will focus on measurements of RNA biology using high-throughput sequencing, which are powerful for their scale but also involve perturbations…
How does learning occur? Neural networks learn via optimization, where a loss function is minimized by a computer to achieve the desired result. But physical networks such as mechanical spring networks or flow networks have no central processor so they cannot minimize such a loss function. An alternative is to encode local rules into those…
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