Computational design and optimization of electro-physiological sensors.

Electro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.

A novel method for automatic single molecule tracking of blinking molecules at low intensities.

Single molecule tracking provides unprecedented insights into diffusional processes of systems in life and material sciences. Determination of molecule positions with high accuracy and correct connection of the determined positions to tracks is a challenging task with, so far, no universal solution for single fluorescing molecules tackling the challenge of low signal-to-noise ratios, frequent blinking and photo bleaching. Thus, the development of novel algorithms for automatic single molecule fluorescence tracking is essential to analyse the huge amount of diffusional data obtained with single molecule widefield fluorescence microscopy. Here, we present a novel tracking model using a top-down polyhedral approach which can be implemented effectively using standard linear programming solvers. The results of our tracking approach are compared to the ground truth of simulated data with different diffusion coefficients, signal-to-noise ratios and particle densities. We also determine the dependency of blinking on the analysed distribution of diffusion coefficients. To confirm the functionality of our tracking method, the results of automatic tracking and manual tracking by a human expert are compared and discussed.

Computing H/D-exchange rates of single residues from data of proteolytic fragments.

BACKGROUND: Protein conformation and protein/protein interaction can be elucidated by solution-phase Hydrogen/Deuterium exchange (sHDX) coupled to high-resolution mass analysis of the digested protein or protein complex. In sHDX experiments mutant proteins are compared to wild-type proteins or a ligand is added to the protein and compared to the wild-type protein (or mutant). The number of deuteriums incorporated into the polypeptides generated from the protease digest of the protein is related to the solvent accessibility of amide protons within the original protein construct. RESULTS: In this work, sHDX data was collected on a 14.5 T FT-ICR MS. An algorithm was developed based on combinatorial optimization that predicts deuterium exchange with high spatial resolution based on the sHDX data of overlapping proteolytic fragments. Often the algorithm assigns deuterium exchange with single residue resolution. CONCLUSIONS: With our new method it is possible to automatically determine deuterium exchange with higher spatial resolution than the level of digested fragments.