News

This video is a year old (and we've previously posted the audio), but looking at this again, a lot is still relevant (and we didn't post the video url), so…

Guest post from Dr. Gregory Bowman, UC Berkeley Two general objectives of the Folding@home project are (1) to explain the molecular origins of existing experimental data and (2) to provide…

Guest post from Dr. Gregory Bowman, UC Berkeley We’ve been making a lot of progress with developing Markov state model (MSM) methods for analyzing the data we generate with the…

Guest post from Dr. Gregory Bowman, UC Berkeley Most rational drug design efforts assume the target protein exists in a single structure and that the structure of one region of…

A brief update to our previous blog post on the A4 bonus: the bonus is now in effect.

We’ve noticed a significant number of high priority projects are trailing behind existing projects. Newer projects are aimed at interpreting and guiding experiments where the full power of Folding@home (F@h)…

Guest post from Dr. Xuhui Huang, Hong Kong University of Science and Technology In this post, I want to introduce a new GPU-powered clustering algorithm we recently developed to analyze…

Guest post from Dr. Vincent Voelz, Temple University Using protein folding simulations alongside experiments remains challenging because the two techniques often "see" very different things. Simulation trajectories "see" every atom…

Guest post from Dr. John Chodera, UC BerkeleyKinases [http://en.wikipedia.org/wiki/Kinase] are the molecular logic gates of the cell.  These important proteins integrate critical signaling information in every cell of our bodies,…