This month’s issue saw the publication of three Education articles: Web Based Computational Education with CHARMMing. In Part I: Lessons and Tutorial, Miller et al. present their freely available, interactive, step-by-step guide for performing common molecular simulation tasks integrated into the CHARMM INterface and Graphics web user interface. Part II: Coarse Grained Protein Folding makes connections between modern molecular simulation techniques and topics commonly presented in advanced undergraduate lectures on physical chemistry, while Part III: Reduction Potentials of Electron Transfer Proteins is a module implemented in the CHARMMing web portal for fast determination of reduction potentials, E°, of redox-active proteins. These articles add a valuable resource on a widely used tool to our popular Education collection, and you can read a blog post about them written by Editor-in-Chief Ruth Nussinov and Guest Editor Qiang Cui here.
An intriguing paper from Attanasi et al. addresses the widespread biological phenomenon of collective behaviour, from cell colonies to flocks of birds. In Collective Behaviour without Collective Order in Wild Swarms of Midges the authors perform three dimensional tracking of large swarms of midges, finding that swarms display strong collective behaviour despite the absence of collective order. The findings of Attanasi et al. suggest that correlation, rather than order, is the true hallmark of collective behaviour in biological systems. We also recommend checking out the mesmerizing supplementary videos of the midge swarms in action.
Finally, a new Software article was added to the collection this month, CeleST: Computer Vision Software for Quantitative Analysis of C. elegans Swim Behavior Reveals Novel Features of Locomotion. Authors Restif et al. report on the first comprehensive computer vision software for analysis of the swimming locomotion of C. elegans. The CeleST software tracks swimming of multiple animals, measures 10 novel parameters of swim behaviour that can fully report dynamic changes in posture and speed, and generates data in several analysis formats, complete with statistics. The authors hope that CeleST will be “a powerful tool for a high-throughput, high-precision analysis of molecules, neuronal circuits, behavior, and plasticity to advance the effort toward understanding dynamic control of behaviour”.