High-end computational services and data management resources are key to sustaining internationally competitive biomedical research. The need for computational infrastructure will become even greater as genomics resources become more sophisticated and ubiquitous (see Genomic Resources Core). This section describes our plan to implement an innovative feedback lifecycle model for providing sustainable computational resources for research program development and customer support services. With NIH investments from previous COBRE awards, we have implemented a state of the art Computational Resources Core (CRC) in the Institute for Bioinformatics and Evolutionary Studies (IBEST) at the University of Idaho. The primary mission of the existing CRC has been to use COBRE funds to develop biomedical research capacity. The CRC currently enables several computationally intensive biomedical research projects, including molecular modeling, statistical simulations, computer algorithm development, and machine learning and data mining.
The aim of this proposed COBRE project is to gradually wean the CRC from COBRE dependence by implementing a business model for fiscal autonomy, without sacrificing flexibility or innovation. The keystone of our plan is to implement a Feedback Lifecycle Model, with two mutually reinforcing pieces: one with purchased equipment for research Program Development and one with leased high-end equipment to support users with independent funding. Our objective is to recruit researchers to develop ideas and preliminary data for future projects on the Program Development system, to perform those projects on the Customer Supported System (leased), and (the key point) to purchase post-lease equipment for the development system while using user fees to maintain the leased systems. COBRE funds will support Program Development operations while we implement the leased system, to improve our data transport hardware and software so that the two systems will be compatible, and to
|de Andrade, Gabriel Belem; Long, Samuel S; Fleming, Harrison et al. (2014) DSCAM localization and function at the mouse cone synapse. J Comp Neurol 522:2609-33|
|Hether, Tyler D; Hohenlohe, Paul A (2014) Genetic regulatory network motifs constrain adaptation through curvature in the landscape of mutational (co)variance. Evolution 68:950-64|
|Stuart, Y E; Campbell, T S; Hohenlohe, P A et al. (2014) Rapid evolution of a native species following invasion by a congener. Science 346:463-6|
|Yang, Lei; Brunsfeld, John; Scott, LuAnn et al. (2014) Reviving the dead: history and reactivation of an extinct l1. PLoS Genet 10:e1004395|
|de Andrade, Gabriel Belem; Kunzelman, Landon; Merrill, Morgan M et al. (2014) Developmentally dynamic colocalization patterns of DSCAM with adhesion and synaptic proteins in the mouse retina. Mol Vis 20:1422-33|
|Hunter, Samuel S; Yano, Hirokazu; Loftie-Eaton, Wesley et al. (2014) Draft Genome Sequence of Pseudomonas moraviensis R28-S. Genome Announc 2:|