Redcraft: Protein Structure Determination from Residual Dipolar Couplings

Wednesday, November 14, 2012 - 11:00 am
SWGN 3A75
PhD Defense - Mikhail Simin In study of diseases and their molecular foundation and evolution, it is critical to study the three dimensional structure of biological macromolecules. Structural characterization of biological macromolecules is further motivated by the fact that biomolecules with defined function(s) exhibit a correlation between their structure and their function. One functional group of bio¬logical macromolecules is proteins: strands of amino acids that form various shapes, and perform various cellular functions. Determining the three dimensional structure of a protein becomes a pivotal point in protein analysis and medicinal studies. Proteins are polymers that are composed of 20 fundamental units of Amino acids. Amino acids vary primarily through their side chain, while sharing nearly identical backbone atoms. In several instances studying the backbone structure of a protein is of significant benefit, as opposed to the all-atom study. It has also been shown that given a protein backbone the side-chains can be places analytically or computationally. One of the advantages of backbone-only study is that obtaining experimental data, such as residual dipolar coupling, is significantly easier than data for side-chains. In the recent years protein structure determination has been assisted by residual dipolar coupling (RDC) data. RDCs show promise as a powerful source for structure determination, not only due to their sensitivity, but also their applicability in macromolecules such as large proteins, membrane-anchored proteins, homo-multimeric protein complexes, carbohydrates, and nucleic acids. Although RDCs are commonly used with a minimum contribution in structure refinement of proteins, their information content extends to de novo structure elucidation. RDCs can be collected fairly easily yet common computational tools do not take maximum advantage of these data. A single RDC datum significantly restrains the possible orientation of a pair of interacting nuclei within a protein; this gives grounds for exploration of minimal data requirements for structure determination. If RDC data are utilized to their maximum potential they can become an informative means of structure determination. This work presents REDCRAFT software package and its advancements in computational structure determination from RDCs. Detailed analyses of the software, and its performance will be presented and discussed in this document. Multiple improvements, as well as new additions to the preceding version of this software will be discussed. In particular, a novel algorithm is presented for solution space decimation addressing REDCRAFT’s native style of search depth selection.

ACM: Android Workshop

Monday, November 12, 2012 - 07:00 pm
swgn 2A31
A quick workshop in Android mobile app development led by Drew Heavner (bring your laptop!). Also, pizza! See Event Page.

Frequent Itemset Mining on FPGA Co-Processor

Monday, November 12, 2012 - 12:30 pm
SWGN 3A75
PhD Defense: Yan Zhang Frequent Itemset Mining (FIM) is a data-mining task that is used to find frequently occurring subsets amongst a database of itemsets. FIM is used in many applications, including those in machine learning and computational biology. In this work, we explore novel hardware architectures to accelerate FIM using multiple Field Programmable Gate Arrays as application-specific coprocessors. In general, FIM is a challenging application to accelerate because it is a data intensive computation and its performance is limited by the available memory bandwidth, and previous work in this area has yielded disappointing results. We develop an efficient hardware accelerator based on ECLAT algorithm. Besides, our approach offers three key advantages to previous efforts. First, we achieve high scalability by dynamically scheduling tasks onto multiple accelerators. Second, we developed a compression scheme for intermediate results and store them onto an on-chip scratchpad memory, significantly reducing the number of off-chip memory accesses. Third, we developed a second data compression scheme for the input data to reduce the total volume of data exchanged over the off-chip memory interface. This compression scheme leverages the bitvector data representation by using a lossless logic minimization-based compression technique that makes single-cycle decoding possible using a novel hardware decoder. Our FPGA coprocessor achieves 29-38 X speedup compared to an optimized x86 implementation. Intermediate compression on scratchpad achieves an additional 2 X speedup, and source bitvector compression achieves an additionally 20-30% speedup.

Android Crash Course

Wednesday, October 24, 2012 - 07:00 pm
SWGN 2a17
A quick crash course in Android mobile app development led by USC grad student Jarrell Waggoner. If you're even vaguely interested in taking a shot at the Appathon (or even if you're not), this is a great way to come out and see how easy it is to get started developing mobile apps with the Android SDK (come on guys, its just java!). Also, pizza! See facebook event.

Dr. Xu: Edison Lecture: Hacking – not Hijacking – Automobiles

Friday, October 19, 2012 - 10:00 am
Swearingen

Hacking – not Hijacking – Automobiles Lecture is at 10am and repeats at noon. Dr. Xu will present her research on hacking a car's tire pressure management system – and how her students messed up her car's instrumentation. Dr. Xu's research interests are in the areas of wireless networks, sensor networks, network security and privacy. She has conducted research into the effect of jamming on commodity wireless networks. Her results have led to link-layer jamming detection mechanisms, as well as link-layer defense strategies to repair networks in the presence of radio interference. More recently, she is investigating the privacy issues in various wireless networks.

Dr O'Kane: Edison Lecture: Robotics

Thursday, October 18, 2012 - 10:00 am
Swearingen

Robotics Lecture is at 10am and repeats at noon. Dr. O'Kane will present the research of his lab, South Carolina Autonomous Robotics Research (SCARR), some of which was mentioned and shown in the Fall 2012 issue of the College's TechnoKids Newsletter. Dr. O'Kane's research is in planning algorithms for robotics and autonomous systems. As robot technology becomes more practical, it becomes increasingly important to design robots that are suitable for domains that are unpredictable and inhospitable, while ensuring that the resulting systems are robust and inexpensive. Because sensing and uncertainty are central issues in robotics, it is essential to understand how to solve robotics problems when sensing is limited and uncertainty is great. Professor O'Kane's interests span sensor-based algorithmic robotics and related areas, including planning under uncertainty, artificial intelligence, computational geometry, sensor networks, and motion planning. See the Edison Lecture Program for more details.

Ontology-driven Data Integration in Biomedicine

Tuesday, October 9, 2012 - 02:30 pm
Swearingen 3A75

COLLOQUIUM Department of Computer Science and Engineering University of South Carolina Ontology-driven Data Integration in Biomedicine GQ Zhang Case Western Reserve University Date: October 9, 2012 Time: 1430-1530 (2:30pm-3:30pm) Place: Swearingen 3A75 Abstract We present an ontology-driven data integration environment called PhysioMIMI (Multi-modality, Multi-resource Information Integration Environment for Physiological and Clinical Research) and illustrate a variety of application scenarios of this environment. PhysioMIMI uses a federated data management approach with a domain ontology as the semantic infrastructure driving data integration, query interface design, and data harmonization across clinical studies. The front-end of PhysioMIMI is a reusable and user-friendly query interface called VISAGE (Visual Aggregator and Explorer). The backend of PhysioMIMI uses an ontology-driven Map and Connect approach, in contrast to the traditional ETL (Extract, Transform and Load) process used in a data warehouse approach. The Map and Connect paradigm embodies flexibility for accommodating data quality improvements in source data by pushing data curation tasks upstream in a source-specific, decentralized way, so that updates can be managed distributively throughout the data reuse life-cycle. Dr. GQ Zhang is Professor of Computer Science and Division Chief of Medical Informatics at Case Western Reserve University's Engineering School and Medical School, respectively. He serves as a Director of Biomedical Informatics Core for CTSC, a member of the Consortium of Clinical Translational Science Award of the National Center for Advancing Translational Sciences, Associate Director of Case Comprehensive Cancer Center, Professor of Proteomics and Bioinformatics and Professor in the Center for Clinical Investigation. His research interests spans Data Management in Biomedicine, Biomedical Ontologies and Applications, Ontology Quality Assurance, Clinical Research Informatics, and Theoretical Computer Science. Dr. Zhang has served on numerous panels, editorial boards and programming committees. He is the author of over 120 publications ranging from automata theory, domain theory, ontology, imaging, to clinical research informatics.

Gamecock Computing Research Symposium

Friday, October 5, 2012 - 02:30 pm
Amoco Hall and the Atrium in front of it

Agenda:

  • Introductions of Dean Ambler, new faculty, and our CSE Staff (this is for the newer students)
  • State of the CSE Department
  • One-Minute Madness (a brief presentation by each CSE faculty member about their research)
  • Poster Session (Ph.D. students, MS students, Magellan Scholars, and select undergraduate students)

Refreshments: (drinks and hors d'oeuvres) to be served during the poster session, which will be held in the area in front of Amoco. This is your opportunity to learn about the world-class research underway in computing at the University of South Carolina. The research extends from the theory of computing to practical aspects, such as smart-phone apps. It includes computer vision, bioinformatics, multiagent systems, Bayesian reasoning, wireless networking, information security, quantum computing, and robotics. The symposium is also an opportunity to meet the students conducting this research. Awards: Best (and runner-up) Graduate Student Poster

Raspberry Pi Lecture

Thursday, October 4, 2012 - 12:30 pm
Open IT Lab at IT-ology
The following is a lecture sponsored by the OpenIT Lab located at IT-ology. Professors and students are invited to a special event at IT-oLogy next Thursday, October 4. Eben Upton, founder and architect of the incredibly popular Raspberry Pi, will speak and be available to take questions. This is a great opportunity to meet Mr. Upton while he is in the U.S. and learn more about the technology itself. What: Eben Upton, founder and trustee of the Raspberry Pi Foundation and the person responsible for the overall software & hardware architecture of the Raspberry Pi device, will visit the Open IT Lab, take a tour and meet with visitors, and will lecture on the Raspberry Pi. The Raspberry Pi is a credit card sized single board computer developed in the UK with the intention of stimulating the teaching of basic computer science in schools. It is open source and has been in worldwide news a lot lately. http://www.engadget.com/2012/05/21/raspberry-pi-hands-on-and-eben-upton… http://www.wired.com/opinion/2012/09/raspberry-pi-insider-exclusive-sel… http://www.theverge.com/culture/2012/8/8/3227564/eben-upton-raspberry-p… When: Next Thursday, October 4 from 12:30 to 2:30 pm 1:00 to 2:30 pm – Taking questions and lecturing on the Raspberry Pi Where: Open IT Lab at IT-oLogy. Everyone planning to attend the Eben Upton presentation needs to register online asap at www.open-it-lab.com/register. Seats are limited to this event.