Privacy-Preserving Reasoning
Privacy-Preserving Reasoning . ISU NSF-Industry-University Cooperative Research Center for Information Protection Read more about Privacy-Preserving Reasoning
Privacy-Preserving Reasoning . ISU NSF-Industry-University Cooperative Research Center for Information Protection Read more about Privacy-Preserving Reasoning
Identifying porcine genes and gene networks involved in effective response to PRRS virus using functional genomics and systems biology. US Department of Agriculture
Future cyber-molecular systems such as biosensors and drug therapeutics must operate safely in a dynamic physical environment. A newly funded project by computer science faculty Robyn Lutz, Jack Lutz, and Jim Lathrop, and GDCB faculty Eric Henderson, will help design cyber-molecular systems that are reliably safe for use.
Read more about CPS:Synergy: Safety-Aware Cyber-Molecular Systems
Abstract:
Computational complexity theory classifies computational problems into various complexity classes based on the amount of resources needed to solve them. This classification is done by measuring various resources such as time, space, nonuniformity, nondeterminism, and randomness. A better understanding of the relationships among these various resources shed light on the computational difficulty of the problems that are encountered in practice. Read more about AF:Small:Collaborative Research:Studies in nonuniformity, completeness, and reachability
University Research Grant, Iowa State University Read more about On Peer-to-Peer Video Services
Matching Funds for PYI Award. Amoco Foundation Read more about Matching Funds for PYI Award
Modeling Secure Web Services with AADL . Center for Information Protection at Iowa State University, NSF Read more about Modeling Secure Web Services with AADL
Evaluation of a Quality Assessment System for Colonoscopy at Iowa Digestive Disease Center (IDDC) . Iowa State University Technology Commercialization Acceleration Program Read more about Evaluation of a Quality Assessment System for Colonoscopy at Iowa Digestive Disease Center
SFS Fellowships for Information Assurance Students. NSF
Read more about SFS Fellowships for Information Assurance Students
Development of Protein Structure Prediction Algorithms. Carver Foundation Read more about Development of Protein Structure Prediction Algorithms
Exploratory Investigation of Modular Ontologies: Research Experiences for Undergraduates Supplement . NSF Read more about Exploratory Investigation of Modular Ontologies: Research Experiences for Undergraduates Supplement
IGERT - Computational Biology Training Group. NSF
Read more about IGERT - Computational Biology Training Group
Supertrees are phylogenies (rooted evolutionary trees) assembled from smaller phylogenies that share some but not necessarily all taxa (leaf nodes) in common. Thus, supertrees can make novel statements about relationships of taxa that do not co-occur on any single input tree while still retaining hierarchical information from the input trees. As a method of combining existing phylogenetic information, supertrees potentially solve many of the problems associated with other methods (e.g., absence of homologous characters, incompatible data types, or non-overlapping sets of taxa). In addition to helping synthesize hypotheses of relationships among larger sets of taxa, supertrees can suggest optimal strategies for taxon sampling (either for future supertree construction or for experimental design issues such as choice of outgroups), can reveal emerging patterns in the large knowledge base of phylogenies currently in the literature, and can provide useful tools for comparative biologists who frequently have information about variation across much broader sets of taxa than those found in any one tree. This web site brings together information and tools to assist phylogenetic biologists and others interested in using supertrees in their research or teaching. It provides background information on the theory and links to examples with real data. It also provides a venue for archiving of software tools for supertree construction as they become available, as well as links to other efforts in this area. Read more about Computational Biology Laboratory
With an interdisciplinary focus, research in our computational structural biology laboratory involves knowledge from multiple disciplines, such as physics, robotics, computer science, and biology. The long-term goal of our research is to understand the functional mechanisms of proteins, and to identify the roles of protein structure and dynamics in the realization of protein function. One of the primary ways in which this goal is being pursued is by developing novel computational methods that are inspired and transferred from research results in other disciplines, such as robotics. Read more about Computational Structural Biology Laboratory
The focus of Formal Methods and Verification Group is to develop formal techniques and tools for automatic verification and analysis of systems.
Read more about Formal Methods & Verification Research Group
Molecular programming, also known as DNA nanotechnology, exploits the information-processing capabilities of nucleic acids to design self-assembling, programmable structures and devices at the nanoscale. Our research is devoted to understanding the power and limitations of this “programming of matter” and using this understanding to make DNA nanotechnology more productive, predictable, and safe. Read more about Laboratory for Molecular Programming
We explore how new software and hardware technologies can assist users with activities of daily living (ADL) in their homes for greater independence and improved quality of life.
Some broad areas of interest in the lab include:
Software Engineering Research Group (SERG) is located in B26, Atanasoff Hall. A cluster of servers and Windows/Mac/Linux, machines are available for conducting research. Visiting scholars, post doctoral researchers and graduate students are seated in various other offices including B26C, B26D, and B26F. A SERG Library is maintained to afford access to archived research material of IEEE, ACM and other publishers that can only be found in hardcopies. Read more about Software Engineering Laboratory
The Laboratory for Wireless Networks and Systems conducts theoretical and systematical research on wireless technologies and applications, with current emphases on heterogeneous integration of wireless systems, power replenishment management and replenishment-aware scheduling for sustainable sensor networks, and security and privacy-preservation for resource-constrained systems. The laboratory is sponsored by Iowa State University, NSF (CSR, CyberTrust and NeTS), Office of Naval Research, and industry companies including Boeing, John Deere, Raytheon and Union Pacific. Read more about Laboratory for Wireless Networks and Systems
Research focused on assessment and prediction frameworks to evaluate software reliability. Read more about Laboratory for Software Safety
The laboratory for software design at Iowa State University conducts research in programming languages, compilers and software engineering. Our overarching goal is to develop tools and techniques that enable better design of software intensive systems: a better design that is easier and cheaper to implement, verify and sustain and that is more portable across computing platform differences.
Wei Le, faculty with the Department of Computer Science, received an NSF grant, as a sole PI to develop fast and on-demand dynamic analysis on code fragments. The award will span three years, and include a total of $485,993. Dynamic analysis is important for many software engineering tasks, such as finding bugs, understanding programs and debugging; however, current dynamic analysis tools are slow and hard to use. The proposed research aims to transform traditional dynamic analysis from analyzing large, monolithic software to analyzing relevant code fragments only. Read more about SHF: Small: Dynamic Analysis on Code Fragments
Our current research focuses on grasping of deformable objects. The problem is very different from grasping rigid ones for which two types of analysis have been developed. Form closure on a rigid object eliminates all of its degrees of freedom, while force closure keeps the object in equilibrium with the ability to resist any arbitrary external wrench. A deformable object, however, has infinite degrees of freedom, which makes form closure impossible. Read more about Robotics Laboratory
Software is an integral part of our everyday lives, and our economy relies heavily on software working correctly. However, bugs in software cause security breaches, and cost our economy billions of dollars annually. While these high costs of bugs are well known, the software industry struggles to remedy the situation because the inherent complexity of the software makes bugs so common that new bugs are typically reported faster than developers can fix them. The goal of this project is to develop a technique that fixes bugs Read more about SHF: EAGER: Collaborative Research: Demonstrating the Feasibility of Automatic Program Repair Guided by Semantic Code Search
Read more about Gentle Colonoscopy with Computer - Guided Navigation
Phylogenetic trees, also known as phylogenies, represent the evolutionary history of sets of species. The construction of such trees is an attempt to understand the origin of life. Phylogenies have several practical uses. For instance, they offer biologists a tool to predict gene function, by comparing and leveraging information among species related by evolution. They also help to track changes in rapidly developing organisms such as viruses or cancer cells. Read more about AF: Small: Algorithms in Phylogenetics
Proteins are fundamental elements of living organisms. They are marvelous microscopic bio-machines that function in a steady, predictable manner. Together with other elements such as DNA, they make up the basics that underlie the complexity of life. The quest to know how these bio-machines work has inspired intense scientific curiosity and imagination. Since most functions are carried out dynamically and are difficult to observe directly from experiments, computational methods have an important, irreplaceable role to play. Read more about CAREER: A Computational Framework for Mapping Ligand Migration Channel Networks and Predicting Molecular Control Mechanisms