activity
20142021
most citedNeural-inspired sensors enable sparse, efficient classification of spatiotemporal data

69 citations · 80 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.SC2021★ 11 cited

Fluid flow in the sarcomere

Sage A Malingen, Kaitlyn Hood, Eric Lauga +2

A highly organized and densely packed lattice of molecular machinery within the sarcomeres of muscle cells powers contraction. Although many of the proteins that drive contraction…

eess.SY2019

Learning Precisely Timed Feedforward Control of the Sensor-Denied Inverted Pendulum

Thomas L. Mohren, Thomas L. Daniel, Steven L. Brunton

Time delays due to signal latency, computational complexity, and sensor-denied environments, pose a critical challenge in both engineered and biological control systems. In this wo…

q-bio.SC2019

A mechanism for sarcomere breathing: volume change and advective flow within the myofilament lattice

Julie A Cass, C. Dave Williams, Tom C Irving +4

During muscle contraction, myosin motors anchored to thick filaments bind to and slide actin thin filaments. These motors rely on energy derived from ATP, supplied, in part, by dif…

math.OC2018★ 69 cited

Neural-inspired sensors enable sparse, efficient classification of spatiotemporal data

Thomas L. Mohren, Thomas L. Daniel, Steven L. Brunton +1

Sparse sensor placement is a central challenge in the efficient characterization of complex systems when the cost of acquiring and processing data is high. Leading sparse sensing m…

q-bio.QM2014

Feedback Control as a Framework for Understanding Tradeoffs in Biology

Noah J. Cowan, Mustafa Mert Ankarali, Jonathan P. Dyhr +7

Control theory arose from a need to control synthetic systems. From regulating steam engines to tuning radios to devices capable of autonomous movement, it provided a formal mathem…