2009 — 2013 |
Catalyurek, Umit V. Huang, Kun Parvin, Jeffrey D [⬀] |
R01Activity Code Description: To support a discrete, specified, circumscribed project to be performed by the named investigator(s) in an area representing his or her specific interest and competencies. |
Informatics Methods For Identifying Breast Cancer Control Genes and Proteins
DESCRIPTION (provided by applicant): This project will develop a new framework for discovery of genes involved in the breast carcinogenesis process. Among families that have a predisposition to breast cancer, approximately 25% have inherited mutations in either breast cancer (BRCA) genes BRCA1 or BRCA2, but the predisposing mutated genes in the majority of the families are unknown. BRCA1 and BRCA2 gene products both regulate cell division pathways that involve DNA repair and centrosome duplication, and their expression is correlated in microarray analyses in many cell types. We hypothesize that other unidentified BRCA genes may be involved in the same pathways that BRCA1 and BRCA2 regulate, and thus may be discovered by identifying genes whose expression also is correlated with that of BRCA1 and BRCA2. We will interrogate public-domain gene expression databases using newly developed computational tools that include combinatorial and algebraic clustering methods to identify genes whose expression correlates with these tumor suppressors. RNA interference will be used to disrupt the expression of the candidate BRCA gene products in two cell-based assays that are dependent on BRCA1 and BRCA2 expression. The first assay models the regulation of homology-directed recombination repair of double-strand DNA breaks, and the second assay tests the control of duplication of the centrosome. We will also perform a third test to determine whether the informatics-identified candidate BRCA gene product can form a protein complex with BRCA1 since several of the already identified co-expressed genes do form a complex with BRCA1. Candidate BRCA genes that are positive in the functional cell based assays will then be tested for changes in expression of their gene products in clinical samples, using an antibody-based, high-throughput tissue microarray system. In summary, this proposal outlines a novel experimental framework that will develop new bioinformatic tools for identifying candidate genes whose regulation suggests the potential for involvement in breast carcinogenesis, testing whether depletion of the proteins encoded by these candidate genes results in phenotypes in the laboratory that are consistent with breast cancer, and determining whether the expression of these candidate genes in clinical samples indicates their potential as biomarkers for breast carcinogenesis. This project defines a framework that may also be applicable to the identification of groups of genes involved in common pathways in other disease processes.
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2012 — 2015 |
Catalyurek, Umit Calyam, Prasad (co-PI) [⬀] Gaitonde, Datta (co-PI) [⬀] Schopis, Paul Whitacre, Caroline [⬀] Panda, Dhabaleswar (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Cc-Nie Integration: Innovations to Transition a Campus Core Cyberinfrastructure to Serve Diverse and Emerging Researcher Needs
The pace of scientific discovery has been rapid in recent years owing to cyberinfrastructures that enable researchers to: (a) remotely access distributed computing resources and big data sets, and (b) effectively collaborate with remote peers, at a global-scale. However, wide-adoption of these advances has been a challenge to researchers mainly due to limitations in traditional cyberinfrastructure equipment, policies and engineering practices at campuses.
This project addresses the adoption challenges for researchers within The Ohio State University (OSU), and for their collaborators at the state, national and international levels. The project team is integrating advanced technologies (e.g., 100Gbps connectivity, perfSONAR, OpenFlow, RoCE/iWARP) relevant to the use cases of diverse OSU researchers in a "Science DMZ" environment. A 100Gbps border router at OSU will be setup to connect to the state-funded OARnet-Internet2 peered 100Gbps network in support of the use cases. The project will investigate the tradeoffs to be balanced between researcher flow performance and campus security practices. Project activities also involve wide-area network experimentation to seamlessly integrate OSU's cyberinfrastructure and Science DMZ with a remote campus (at University of Missouri) cyberinfrastructure. This project will create and document the role of a "Performance Engineer on campus", who will be the primary "keeper" and "help-desk" of the Science DMZ equipment, and will function as a liaison with researchers and their collaborators to configure wide-area cyberinfrastructures. Best-practices are to be published, and open-source software applications will be developed for handling researcher application flows in production networks across diverse science/engineering disciplines and multiple university campuses.
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0.915 |
2015 — 2017 |
Catalyurek, Umit |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Collaborative Research: Innovative Ab Initio Symmetry-Adapted No-Core Shell Model For Advancing Fundamental Physics and Astrophysics
A team of researchers at Louisiana State University will address the significant computational challenges inherent to modeling the intricate dynamics of atomic nuclei, which are fundamental to a vast array of astrophysical phenomena. They will do so by employing the petascale resources of the Blue Waters Supercomputer. More specifically, the investigators will carry out large-scale computations of intermediate-mass nuclei from oxygen to argon, including exotic unstable isotopes that are the focus of current and next-generation rare isotope experimental facilities. Such nuclei are often found key to understanding processes in extreme environments, from stellar explosions to the interior of nuclear reactors. Reliable nuclear structure information provided by this research project will have impacts on basic research questions in astrophysics and neutrino physics, and will also have potential applications in areas like nuclear energy, thus contributing to the nation's energy infrastructure. Training in utilizing large-scale computational resources will be provided to, the next generation of physicists, and the team will expand the impact of their research by providing nuclear structure information of unprecedented accuracy and scope as a publicly available database for use by other scientists.
The LSU team's approach is to solve the Schrodinger equation for a many-body quantum system composed of protons and neutrons interacting via realistic interactions that are tied to the underlying quark/gluon considerations. The solution to this problem is achieved by finding eigenstates and eigenvalues of the nuclear Hamiltonian, which is computed in a physically relevant basis that capitalizes on exact and approximate symmetries of nuclei. The use of such symmetries is a unique feature of our model, one that coupled with the Blue Waters capabilities makes solutions feasible. Namely, the team will employ the symmetry-adapted no-core shell model approach implemented by a highly scalable computer code, dubbed "LSU3shell", that has already demonstrated good scalability and performance on the Blue Waters system. Calculations will provide nuclear properties of short-lived neutron-deficient and neutron-rich isotopes with little to no available experimental data that are expected to have a considerable impact on modeling X-ray burst observables, on triggering processes responsible for the synthesis of many of the heavy elements present in the universe, and on providing a stringent test of fundamental symmetries in nature and physics beyond the Standard model.
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0.915 |
2015 — 2018 |
Catalyurek, Umit Zhang, Xiaodong (co-PI) [⬀] Agrawal, Gagan [⬀] Panda, Dhabaleswar (co-PI) [⬀] Sadayappan, Ponnuswamy (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Ii-New: Infrastructure For Energy-Aware High Performance Computing (Hpc) and Data Analytics On Heterogeneous Systems
The project builds a comprehensive research infrastructure to meet the needs of a large research team at the Ohio State University allowing experimental research in a number of computer science areas including high performance computing, data analytics, storage, and virtualization. The project will lead to significant advances in many computer science areas, and its impact will be enhanced through active dissemination of software from the investigators. The project will contribute substantially to human resource development, education in computer science increasing diversity in related areas.
More specifically, researchers will acquire and deploy an infrastructure that includes three types of accelerators, conventional as well as energy-efficient nodes, large main memory including Solid State Drive (SSD) on a subset of nodes, and hardware for fine-grained power measurements. The requested resources will allow experimentation with a number of popular or emerging cluster configurations that address needs of a variety of compute-intensive and/or data-intensive workloads. Such an internally hosted and reconfigurable cluster will also allow power measurements, voltage margin reduction experiments, and failure detection and recovery studies in the presence of physical failures - none of which is typically feasible at national supercomputing and cloud infrastructures. The infrastructure is motivated by the multiple paradigm shifts that high performance computing is presently undergoing. They include increasing use of accelerators or coprocessors, increased criticality of energy and resilience beyond performance, synergy with data analytic applications, and popularity of massive main memory or SSD technologies. These trends provide opportunities and challenges for a variety of scientific, medical, and enterprise applications to be explored in this project.
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0.915 |
2015 |
Catalyurek, Umit V. Payne, Philip R.o. [⬀] |
T15Activity Code Description: To assist professional schools and other public and nonprofit institutions to establish, expand, or improve programs of continuing professional education, especially for programs of extensive continuation, extension, or refresher education dealing with new developments in the science of technology of the profession. |
Midas: Multi-Modeling and Integrative Data Analytics Training Program
? DESCRIPTION (provided by applicant): The purpose of the proposed project, entitled MIDAs: Multi-modeling and Integrative Data Analytics Training Program, is to extend and enhance a novel Biomedical Informatics training initiative at The Ohio State University that focuses upon the emergent and rapidly growing Biomedical Informatics sub-domains of Translational Bioinformatics (TBI) and Clinical Research Informatics (CRI). This extended program will augment such scholarly focus areas with additional curricula relevant to the application of data science and analytics principles to the two preceding areas, thus accelerating the pace and impact of the research activities conducted by targeted trainees in the era of big data as it applies to biomedicine. MIDAs will leverage the unique scholarly and environmental strengths present at The Ohio State University Wexner Medical Center (OSUWMC), as well as the broader computational and data analytics expertise that spans the campus of The Ohio State University. Trainees will be involved in a combination of didactic and application-oriented instruction modalities, and will pursue independent research projects as a capstone to their curricula. Of note, such research projects will incorporate opportunities for experiential learning and investigation beyond the traditional academic environment through a unique set of public-private partnerships with data analytics focused organizations in the Central Ohio region. The MIDAs training program will house an additional six pre- doctoral trainees, complementing the existing pre- and post-doctoral trainee cohort already engaged in Biomedical Informatics training at The Ohio State University as part of an NLM-funded T15 training award. Our intent with the MIDAs program is to utilize an agile and highly innovative curricula development and evaluation plan, thus allowing for constant program optimization and adaptation to evolving trends and developments in the basic and applied Biomedical Informatics and Data Science knowledge bases.
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