Theory & Algorithms
Most CISE research projects include elements of theoretical analysis and algorithm development. These projects study the capabilities and fundamental limitations of algorithms to better understand the computational tools utilized in various research fields. Researchers apply this knowledge to machine learning, data structures, optimization, computational biology, cryptography,geometric modeling, and other fields. Theory and algorithms anticipates the growing quantity and power of data and works to use algorithms to their full capacity. Research areas include: designing efficient data structure and algorithms, understanding the complexity of computational problems, and designing secure cryptographic systems.
SHB: Type II (INT): Collaborative Research: Algorithmic Approaches to Personalized Health Care
The US health care system spends major resources on the treatment of acute conditions in a hospital setting rather than focusing on prevention and keeping patients out of the hospital. While there is no broad agreement on the potential solutions, structural reform is on the horizon. The meaningful use of Electronic Health Records (EHRs) is […]
CIF: Small: Sensing-Aware Decision Making for High-Dimensional Signals
There has been an explosion in our ability to sense and record the world around us. This has led to new discoveries and allowed us to consider new paradigms in nearly every walk of life. While the promise of these developments is significant, the explosion of sensing has also created substantial challenges. These challenges include […]
ABI Development: Refinement Algorithms and Server for Protein Docking
Protein-protein interactions are integral to virtually all biological pathways. Predicting these interactions and the function of the protein complex in key to understanding how biological pathways function. Detailed multistage docking algorithms, which starts from the unbound structures of two proteins, can determine the structure of the protein complex. The docking server, ClusPro, strives to make […]
High-dimensional Discrete Inference
Recent advances in the last decade have brought attention to the analysis of high-dimensional data and, in particular, to estimation on high-dimensional spaces. Such spaces are often structured by either exhibiting constraints on specific space components or by the incorporation of prior information identifying co-dependence patterns between components in order to help carrying out the […]
Refinement Methods for Protein Docking based on Exploring Multi-Dimensional Energ
All successful state-of-the-art protein docking methods employ a so called multistage approach. At the first stage of such approaches a rough energy potential is used to score billions of conformations. At a second stage, thousands of conformations with the best scores are retained and clustered based on a certain similarity metric. Cluster centers correspond to […]
Computational mapping of proteins for the binding of ligands
The proposal requests the renewal of the grant “Computational Mapping of Proteins for the Binding of Ligands”. Mapping globally samples the surface of target proteins using fragment sized molecular probes. The general goals of mapping are determining binding hot spots, i.e., regions of proteins that are major contributors to the binding free energy, and identifying […]