News & Announcements

  • Model-, structure-, and sequence-based methods for prediction of protein binding sites

    Identification of protein-protein binding sites is important in understanding the protein function. The binding site prediction methods that rely on structure are generally more accurate than those ones relying on sequence. However, the coverage of structure-based methods is significantly lower than of the sequence-based method due to the lack of experimental structures. Here, we propose…

  • Sequence Identity Study for Operational Taxonomic Unit Classification

    In metagenomics studies of microorganisms, Operational Taxonomic Unit (OTU) is often used as the replacement for species distinction. This pseudo-species definition is helpful in cases when the scientists would like to understand the composition and diversity of the culture in different environments. Traditional numerical taxonomy method typically defines an OTU as a cluster in a…

  • Predictive Analytics On Medicare/Medicade Cost Outcomes

    LIGHT2 (Leveraging Information Technology for Hi-Tech and Hi-Touch Care) is a federally funded project using 24 “Nurse Care Managers” to manage the health of 10,000 Medicare and Medicaid patients. Its goal is to reduce exacerbations of chronic diseases, which would improve health outcomes while lowering healthcare costs. Analytics support (“Hi-Tech”) support for the Nurse Care…

  • A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction

    The necessity for reliable ab initio protein secondary structure prediction is growing along with the demand for accurate tertiary structure prediction. Although recent developments have slightly exceeded previous methods of secondary structure prediction, these methods rarely surpass 80% accuracy. Developing new tools and methods to improve secondary structure prediction is essential to the improvement of…

  • Automated Large-Scale File Preparation and Docking: Evaluation of ITScore and STScore Using the 2012 Community Structure−Activity Resource Benchmark

    We present the first study utilizing the full set of compounds from the recently released 2012 Community Structure−Activity Resource (CSAR) data set. The CSAR data set is a realistic benchmark for protein-ligand docking scoring functions, containing 57 crystal structures and 757 compounds, most with known affinities from pharmaceutical companies. We used the CSAR data set…

  • Simulation based Training for Medical Skills: Comparative Effectiveness of Training Methods and Evaluating the Translational Impact

    Simulation based medical education is gaining wide spread appeal as a means to increase medical skill training opportunities and enhance patient safety in a changing medical environment. Two factors have accelerated the adoption of patient simulation in health care including; 1) the successful use of simulation in other high risk endeavors such as airline pilot…

  • Large-Scale Pairwise Alignments on GPU Clusters: Exploring the Implementation Space

    Several problems in computational biology require the all-against-all pairwise comparisons of tens of thousands of individual biological sequences. Each such comparison can be performed with the well-known Needleman-Wunsch alignment algorithm. However, with the rapid growth of biological databases, performing all possible comparisons with this algorithm in serial becomes extremely time-consuming. The massive computational power of…

  • TeleMDID: Mobile Technology Applications for Interactive Diagnoses in Teledermatology

    A web-based dermatology image management application, Missouri Dermatology Image Database (MDID), has been developed to facilitate dermatology practices. The digital images captured offsite are transferred to MDID’s secure server via encrypted connection and user authentication. Uploaded images can be organized by multiple criteria, and patients and images can be easily searched. Originally, the MDID database…

  • A Study of User Behaviors in Web-based Medical Image Management and Search

    Medical professionals in various specialties work closely with digital images for diagnosis, research and education. Electronic applications of image management are emerging in virtually every medical specialty, including cardiology, radiology, pathology, dermatology, orthopedics, OB/GYN etc.  Compared to radiology, there is a less well-established adoption of such applications as PACS in dermatology in daily practices. Mizzou…