Project description:Collecting and managing data for clinical and translational research presents significant challenges for clinical and translational researchers, many of whom lack needed access to data management expertise, methods, and tools. At many institutions, funding constraints result in differential levels of research informatics support among investigators. In addition, the lack of widely shared models and ontologies for clinical research informatics and health information technology hampers the accurate assessment of investigators' needs and complicates the efficient allocation of crucial resources for research projects, ultimately affecting the quality and reliability of research. In this paper, we present a model for providing flexible, cost-efficient institutional support for clinical and translational research data management and informatics, the research management team, and describe our initial experiences with deploying this model at our institution.
Project description:A number of state-of-the-art protein structure prediction servers have been developed by researchers working in the Bioinformatics Unit at University College London. The popular PSIPRED server allows users to perform secondary structure prediction, transmembrane topology prediction and protein fold recognition. More recent servers include DISOPRED for the prediction of protein dynamic disorder and DomPred for domain boundary prediction. These servers are available from our software home page at http://bioinf.cs.ucl.ac.uk/software.html.
Project description:The UCL Bioinformatics Group web portal offers several high quality protein structure prediction and function annotation algorithms including PSIPRED, pGenTHREADER, pDomTHREADER, MEMSAT, MetSite, DISOPRED2, DomPred and FFPred for the prediction of secondary structure, protein fold, protein structural domain, transmembrane helix topology, metal binding sites, regions of protein disorder, protein domain boundaries and protein function, respectively. We also now offer a fully automated 3D modelling pipeline: BioSerf, which performed well in CASP8 and uses a fragment-assembly approach which placed it in the top five servers in the de novo modelling category. The servers are available via the group web site at http://bioinf.cs.ucl.ac.uk/.