Physical Sciences and Mathematics Commons^™

Fully Generalized Two-Dimensional Constrained Delaunay Mesh Refinement, Panagiotis A. Foteinos, Andrey N. Chernikov, Nikos P. Chrisochoides

Computer Science Faculty Publications

Traditional refinement algorithms insert a Steiner point from a few possible choices at each step. Our algorithm, on the contrary, defines regions from where a Steiner point can be selected and thus inserts a Steiner point among an infinite number of choices. Our algorithm significantly extends existing generalized algorithms by increasing the number and the size of these regions. The lower bound for newly created angles can be arbitrarily close to $30^{\circ}$. Both termination and good grading are guaranteed. It is the first Delaunay refinement algorithm with a $30^{\circ}$ angle bound and with grading guarantees. Experimental evaluation of our algorithm …

Structure Prediction For The Helical Skeletons Detected From The Low Resolution Protein Density Map, Kamal Al Nasr, Weitao Sun, Jing He

Computer Science Faculty Publications

Background: The current advances in electron cryo-microscopy technique have made it possible to obtain protein density maps at about 6-10 Å resolution. Although it is hard to derive the protein chain directly from such a low resolution map, the location of the secondary structures such as helices and strands can be computationally detected. It has been demonstrated that such low-resolution map can be used during the protein structure prediction process to enhance the structure prediction.

Results: We have developed an approach to predict the 3-dimensional structure for the helical skeletons that can be detected from the low resolution protein density …

Improving Predicted Protein Loop Structure Ranking Using A Pareto-Optimality Consensus Method, Yaohang Li, Ionel Rata, See-Wing Chiu, Erik Jakobsson

Computer Science Faculty Publications

Background

Accurate protein loop structure models are important to understand functions of many proteins. Identifying the native or near-native models by distinguishing them from the misfolded ones is a critical step in protein loop structure prediction.

Results

We have developed a Pareto Optimal Consensus (POC) method, which is a consensus model ranking approach to integrate multiple knowledge- or physics-based scoring functions. The procedure of identifying the models of best quality in a model set includes: 1) identifying the models at the Pareto optimal front with respect to a set of scoring functions, and 2) ranking them based on the fuzzy …