MRI/Acq.: Computing Equipment for Supporting Data-intensive Bioinformatics Research Project Proposed: This project, acquiring a multicore hybrid cyberinfrastructure instrument, aims to enable and empower several lines of research requiring processing and/or storage of big and complex data. The equipment services critical areas in data and computing intensive bioinformatics research, mainly high-throughput sequencing data analysis, molecular dynamics simulation, cell signaling and molecular recognition, computational chemical biology environmental and evolutionary biology. Providing an open, extensible, and scalable platform to support data-intensive science programs, the instrumentation serves as a testbed for computing and simulation methodology development utilizing advanced multi-core architecture as well as supporting large-scale data analysis needs. The project responds to the clear trend towards data driven science, in which large amounts of information coming from instruments for automated sequencing, high throughput screening systems, and other high volume analysis techniques, is mined and analyzed to look for patterns from which hypotheses can be developed. Along with data-driven science as a source of insights, detailed modeling and simulation of biological structures and processes are becoming indispensable tools to test models, to evaluate experimental methodologies, and to interpret the results. Evaluation and interpretation drive the need across a broad spectrum of research. This acquisition supports the current need and near-term research goals and aims to maintain a forward position in computationally intensive research. Broader Impacts: The instrumentation impacts the research it enables. It is also well aligned to the institution?s strategic initiative it enables and contributes in seeking other research opportunity initiatives such as BigData and XSEDE (eXtreme Science and Engineering Discovery Environment). The equipment enhances research opportunities for graduate students, increasing opportunities for student to gain experience in parallel computing as part of course work, and establishes a broader high-performance parallel computing base within the institution and the surrounding region. The School of Engineering?s Diversity Programs will help identify qualified students from underrepresented groups and assist with the recruitment and retention for women and minorities possibly with scholarships. The computing resource should have significant impact in the region. Working with the Kansas IDeA Network for Biomedical Research Excellence Bioinformatics core, bioinformatics expertise will be delivered to minority and undergraduate-serving schools.
