WebLogo 3.3 web-sever
WebLogo 3.3 code
[Gavin Crooks, David Sivak]
* Improved the algorithm that guesses the sequence type (DNA, RNA or protein) (Kudos: Bug report, Roland Pache )
* Fixed an issue with reading transfac matrices with alternative alphabets(Kudos: Bug report, Nima Emami )
* Fixed Motif.reindex()
* Implemented Motif.reverse() and Motif.complement() (Can now reverse complement transfac matrix input on the command
line.) (Kudos: Feature request, Seth P Boudreaux )
* Command line interface now automagically recognizes transfac files.
* Add command line option “–reverse-stacks NO” which inverts the logo stacks so that the most conserved monomers are at the bottom of the stack, rather than the top. This ordering is consistent with the standard ordering for histograms, and is arguably a better representation. (Kudos: Luke Hutchison )
* Fixed an issue so that the correct color scheme is chosen for the specified sequence type.
* Miscellaneous minor bug fixes and refactoring.
David A. Sivak, Gavin E. Crooks, Phys. Rev. Lett., 108, 190602 (2012)
[ Full Text | Journal | arXiv ]
This is mostly David’s creation, from inception to conclusion, although I like to think I’ve contributed some elegant prose. Essentially, he shows that at the intersection of linear response theory and thermodynamic length analysis, there is a really nice framework for understanding optimal protocols for driving thermodynamic systems. Continue reading
David A. Sivak, Gavin E. Crooks. Phys. Rev. Lett. 108, 150601 (2012)
[ Full Text | Journal ]
Abstract: A central endeavor of thermodynamics is the measurement of free energy changes. Regrettably, although we can measure the free energy of a system in thermodynamic equilibrium, typically all we can say about the free energy of a non-equilibrium ensemble is that it is larger than that of the same system at equilibrium. Herein, we derive a formally exact expression for the probability distribution of a driven system, which involves path ensemble averages of the work over trajectories of the time-reversed system. From this we find a simple near-equilibrium approximation for the free energy in terms of an excess mean time-reversed work, which can be experimentally measured on real systems. With analysis and computer simulation, we demonstrate the accuracy of our approximations for several simple models.
Version: 0.4 BETA
In a desperate attempt to preserve my own sanity, a survey of probability distributions used to describe a single, continuous, unimodal, univariate random variable.
[ Full Text ]
Jerome P. Nilmeier, Gavin E. Crooks, David L. D. Minh, and John D. Chodera, Proc. Natl. Acad. Sci. U.S.A. (2011) 108(45) E1009-E1018
[ Full text | Journal | Author summary | Errata ]
This was a fun paper that originated in a chance, serendipitous conversation between myself, Jerome and John. We realized that several different Monte Carlo sampling techniques that we had each recently worked on could be unified under a common framework by taking inspiration from nonequilibrium thermodynamics. (I am also particularly satisfied with the joke. I firmly believe every scientific paper should contain one joke, lest we take ourselves too seriously. This one is great because it’s hiding in plain sight.)
Abstract: Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also rapidly sample uncorrelated configurations. Continue reading
Here’s to the crazy ones. The misfits. The rebels. The troublemakers. The round pegs in the square holes. The ones who see things differently. They’re not fond of rules. And they have no respect for the status quo. You can quote them, disagree with them, glorify or vilify them. About the only thing you can’t do is ignore them. Because they change things. They push the human race forward. And while some may see them as the crazy ones, we see genius. Because the people who are crazy enough to think they can change the world, are the ones who do.
“Whither time’s arrow?”
Setting Time Aright
An international and inter-disciplinary meeting investigating the Nature of Time
Foundational Questions Institute
Norway and Denmark,
Aug. 27 – Sept. 1, 2011
♬ I’m on a
boat ship and it’s going fast and … ♬
Gavin E. Crooks, J. Stat. Mech. (2011) P07008
[ Full Text | Journal ]
Abstract: The word ‘reversible’ has two (apparently) distinct applications in statistical thermodynamics. A thermodynamically reversible process indicates an experimental protocol for which the entropy change is zero, whereas the principle of microscopic reversibility asserts that the probability of any trajectory of a system through phase space equals that of the time reversed trajectory. However, these two terms are actually synonymous: a thermodynamically reversible process is microscopically reversible, and vice versa.
Gavin E. Crooks and David A. Sivak, J. Stat. Mech.: Theor. Exp. P06003 (2011)
[ Full Text | Journal ]
I’ve been meaning to look at the physical significance of f-divergences for some time. These are a class of information type measures that, thanks to the quirks of nonequilibrium thermodynamics, can actually be experimentally measured in real systems. I was finally inspired to write this up due to John Baez, who recently discussed the significance of Rényi entropy to equilbrium statistical mechanics.
Abstract: Many interesting divergence measures between conjugate ensembles of nonequilibrium trajectories can be experimentally determined from the work distribution of the process. Herein, we review the statistical and physical significance of several of these measures, in particular the relative entropy (dissipation), Jeffreys divergence (hysteresis), Jensen–Shannon divergence (time-asymmetry), Chernoff divergence (work cumulant generating function), and Rényi divergence.
“Near equilibrium measurements of non-equilibrium free energies”
2010 Workshop on
Multiscale Molecular Modeling: Molecular Dynamics, Computational Statistical Mechanics, and Simulation Algorithms
University of Edinburgh.