Google-Accelerated Biomolecular Simulations.

Biomolecular simulations rely heavily on the availability of suitable compute infrastructure for data-driven tasks like modeling, sampling, and analysis. These resources are typically available on a per-lab and per-facility basis, or through dedicated national supercomputing centers. In recent years, cloud computing has emerged as an alternative by offering an abundance of on-demand, specialist-maintained resources that enable efficiency and increased turnaround through rapid scaling.

Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways.

Simulations can provide tremendous insight into the atomistic details of biological mechanisms, but micro- to millisecond timescales are historically only accessible on dedicated supercomputers. We demonstrate that cloud computing is a viable alternative that brings long-timescale processes within reach of a broader community. We used Google's Exacycle cloud-computing platform to simulate two milliseconds of dynamics of a major drug target, the G-protein-coupled receptor β2AR.

CAMPAIGN: an open-source library of GPU-accelerated data clustering algorithms.

Motivation: Data clustering techniques are an essential component of a good data analysis toolbox. Many current bioinformatics applications are inherently compute-intense and work with very large datasets. Sequential algorithms are inadequate for providing the necessary performance.

The iFly tracking system for an automated locomotor and behavioural analysis of Drosophila melanogaster.

The use of animal models in medical research provides insights into molecular and cellular mechanisms of human disease, and helps identify and test novel therapeutic strategies. Drosophila melanogaster--the common fruit fly--is one of the most well-established model organisms, as its study can be performed more readily and with far less expense than for other model animal systems, such as mice, fish, or primates. In the case of fruit flies, standard assays are based on the analysis of longevity and basic locomotor functions.

Detection of early locomotor abnormalities in a Drosophila model of Alzheimer's disease.

Behavioural assays represent sensitive methods for detecting neuronal dysfunction in model organisms. A number of manual methods have been established for Drosophila, however these are time-consuming and generate parameter-poor phenotype descriptors. Here, we have developed an automated computer vision system to monitor accurately the three-dimensional locomotor trajectories of flies.

Fast and accurate predictions of protein NMR chemical shifts from interatomic distances.

We present a method, CamShift, for the rapid and accurate prediction of NMR chemical shifts from protein structures. The calculations performed by CamShift are based on an approximate expression of the chemical shifts in terms of polynomial functions of interatomic distances. Since these functions are very fast to compute and readily differentiable, the CamShift approach can be utilized in standard protein structure calculation protocols.