Learning biophysics with open simulations

Biophysics.

Single-molecule Biophysics: Machine Learning for Automated Data Processing

Single-molecule fluorescence microscopy has been greatly successful in understanding biophysics at molecular level. This technique has been advancing toward higher throughput, which creates a need for a data-analysis tool to distinguish molecule of interest from other fluorescence signals. Here, we have used supervised machine-learning approaches to filter biological events of our interest, and...

Computational Biophysics

Introduction/Group Overview The RLE Computational Biophysics Group is focused on understanding conformational changes in biomolecules that play an important role in common human diseases. The group uses an interdisciplinary approach combining computational modeling with biochemical experiments to make connections between conformational changes in macromolecules and disease progression. By emplo...

Radiation Biophysics

As valuable as the formal presentations are the informal and thoughtprovoking discussions which are well reported in the published proceedings. The booklet will be rewarding reading for those interested in the mode of action of neuromuscular blocking agents. In addition, the consideration given to drug receptor interaction, although naturally applied to the curare receptor, should prove very us...

Biophysics Letter

Many cell movements appear to be driven by the polymerization of actin. Here we show how the force of polymerization can be generated by the thermal motions of the actin filaments near the sites of polymerization. We apply the model to explain the observations that the lamel-lipodial cytoskeleton is organized into an orthogonal network interspersed with filopodial protrusions, and that the prot...