Project description:BackgroundClinical and Translational Research (CTR) requires a team-based approach, with successful teams engaging in skilled management and use of information. Yet we know little about the ways that Translational Teams (TTs) engage with information across the lifecycle of CTR projects. This qualitative study explored the challenges that information management imposes on the conduct of team-based CTR.MethodsWe conducted interviews with ten members of TTs at University of Wisconsin. Interviews were transcribed and thematic analysis was conducted.ResultsTTs' piecemeal and reactive approaches to information management created conflict within the team and slowed scientific progress. The lack of cohesive information management strategies made it more difficult for teams to develop strong team processes like communication, scientific coordination, and project management. While TTs' research was hindered by the institutional challenges of interdisciplinary team information sharing, TTs who had developed shared approaches to information management that foregrounded transparency, accountability, and trust, described substantial benefits to their teamwork.ConclusionWe propose a new model for the Science of Team Science field - a Translational Team Science Hierarchy of Needs - that suggests interventions should be targeted at the appropriate stage of team development in order to maximize a team's scientific potential.
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.