XSEDE: Accelerating Scientific Discovery
01 Sep 2014-Vol. 16, Iss: 5, pp 62-74
TL;DR: XSEDE's integrated, comprehensive suite of advanced digital services federates with other high-end facilities and with campus-based resources, serving as the foundation for a national e-science infrastructure ecosystem.
Abstract: Computing in science and engineering is now ubiquitous: digital technologies underpin, accelerate, and enable new, even transformational, research in all domains. Access to an array of integrated and well-supported high-end digital services is critical for the advancement of knowledge. Driven by community needs, the Extreme Science and Engineering Discovery Environment (XSEDE) project substantially enhances the productivity of a growing community of scholars, researchers, and engineers (collectively referred to as "scientists"' throughout this article) through access to advanced digital services that support open research. XSEDE's integrated, comprehensive suite of advanced digital services federates with other high-end facilities and with campus-based resources, serving as the foundation for a national e-science infrastructure ecosystem. XSEDE's e-science infrastructure has tremendous potential for enabling new advancements in research and education. XSEDE's vision is a world of digitally enabled scholars, researchers, and engineers participating in multidisciplinary collaborations to tackle society's grand challenges.
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TL;DR: Improvements to Galaxy's core framework, user interface, tools, and training materials enable Galaxy to be used for analyzing tens of thousands of datasets, and >5500 tools are now available from the Galaxy ToolShed.
Abstract: Galaxy (homepage: https://galaxyproject.org, main public server: https://usegalaxy.org) is a web-based scientific analysis platform used by tens of thousands of scientists across the world to analyze large biomedical datasets such as those found in genomics, proteomics, metabolomics and imaging. Started in 2005, Galaxy continues to focus on three key challenges of data-driven biomedical science: making analyses accessible to all researchers, ensuring analyses are completely reproducible, and making it simple to communicate analyses so that they can be reused and extended. During the last two years, the Galaxy team and the open-source community around Galaxy have made substantial improvements to Galaxy's core framework, user interface, tools, and training materials. Framework and user interface improvements now enable Galaxy to be used for analyzing tens of thousands of datasets, and >5500 tools are now available from the Galaxy ToolShed. The Galaxy community has led an effort to create numerous high-quality tutorials focused on common types of genomic analyses. The Galaxy developer and user communities continue to grow and be integral to Galaxy's development. The number of Galaxy public servers, developers contributing to the Galaxy framework and its tools, and users of the main Galaxy server have all increased substantially.
2,601 citations
Cites methods from "XSEDE: Accelerating Scientific Disc..."
...Specifically, Galaxy Main is now configured to take advantage of the XSEDE infrastructure (8) that includes Bridges and Stampede resources as well as the Jetstream cloud (9)....
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TL;DR: iDEP helps unveil the multifaceted functions of p53 and the possible involvement of several microRNAs such as miR-92a, miR/Bioconductor packages, 2 web services, and comprehensive annotation and pathway databases for 220 plant and animal species.
Abstract: RNA-seq is widely used for transcriptomic profiling, but the bioinformatics analysis of resultant data can be time-consuming and challenging, especially for biologists. We aim to streamline the bioinformatic analyses of gene-level data by developing a user-friendly, interactive web application for exploratory data analysis, differential expression, and pathway analysis. iDEP (integrated Differential Expression and Pathway analysis) seamlessly connects 63 R/Bioconductor packages, 2 web services, and comprehensive annotation and pathway databases for 220 plant and animal species. The workflow can be reproduced by downloading customized R code and related pathway files. As an example, we analyzed an RNA-Seq dataset of lung fibroblasts with Hoxa1 knockdown and revealed the possible roles of SP1 and E2F1 and their target genes, including microRNAs, in blocking G1/S transition. In another example, our analysis shows that in mouse B cells without functional p53, ionizing radiation activates the MYC pathway and its downstream genes involved in cell proliferation, ribosome biogenesis, and non-coding RNA metabolism. In wildtype B cells, radiation induces p53-mediated apoptosis and DNA repair while suppressing the target genes of MYC and E2F1, and leads to growth and cell cycle arrest. iDEP helps unveil the multifaceted functions of p53 and the possible involvement of several microRNAs such as miR-92a, miR-504, and miR-30a. In both examples, we validated known molecular pathways and generated novel, testable hypotheses. Combining comprehensive analytic functionalities with massive annotation databases, iDEP (
http://ge-lab.org/idep/
) enables biologists to easily translate transcriptomic and proteomic data into actionable insights.
618 citations
TL;DR: This review is a comprehensive description of the molecular and morphological parameters that govern the mechanical properties of organic semiconductors and describes how low modulus, good adhesion, and absolute extensibility prior to fracture enable robust performance, along with mechanical "imperceptibility" if worn on the skin.
Abstract: Mechanical deformability underpins many of the advantages of organic semiconductors. The mechanical properties of these materials are, however, diverse, and the molecular characteristics that permit charge transport can render the materials stiff and brittle. This review is a comprehensive description of the molecular and morphological parameters that govern the mechanical properties of organic semiconductors. Particular attention is paid to ways in which mechanical deformability and electronic performance can coexist. The review begins with a discussion of flexible and stretchable devices of all types, and in particular the unique characteristics of organic semiconductors. It then discusses the mechanical properties most relevant to deformable devices. In particular, it describes how low modulus, good adhesion, and absolute extensibility prior to fracture enable robust performance, along with mechanical “imperceptibility” if worn on the skin. A description of techniques of metrology precedes a discussion...
543 citations
TL;DR: Nitrogen- and ruthenium-codoped carbon nanowires are prepared as effective hydrogen evolution catalysts in which r Ruthenium atoms in a carbon matrix drive electrocatalysis of hydrogen evolution.
Abstract: Hydrogen evolution reaction is an important process in electrochemical energy technologies. Herein, ruthenium and nitrogen codoped carbon nanowires are prepared as effective hydrogen evolution catalysts. The catalytic performance is markedly better than that of commercial platinum catalyst, with an overpotential of only -12 mV to reach the current density of 10 mV cm-2 in 1 M KOH and -47 mV in 0.1 M KOH. Comparisons with control experiments suggest that the remarkable activity is mainly ascribed to individual ruthenium atoms embedded within the carbon matrix, with minimal contributions from ruthenium nanoparticles. Consistent results are obtained in first-principles calculations, where RuCxNy moieties are found to show a much lower hydrogen binding energy than ruthenium nanoparticles, and a lower kinetic barrier for water dissociation than platinum. Among these, RuC2N2 stands out as the most active catalytic center, where both ruthenium and adjacent carbon atoms are the possible active sites.
393 citations
TL;DR: Large-scale benchmark tests show that the new hybrid COFACTOR approach significantly improves the function annotation accuracy of the former structure-based pipeline and other state-of-the-art functional annotation methods, particularly for targets that have no close homology templates.
Abstract: The COFACTOR web server is a unified platform for structure-based multiple-level protein function predictions. By structurally threading low-resolution structural models through the BioLiP library, the COFACTOR server infers three categories of protein functions including gene ontology, enzyme commission and ligand-binding sites from various analogous and homologous function templates. Here, we report recent improvements of the COFACTOR server in the development of new pipelines to infer functional insights from sequence profile alignments and protein-protein interaction networks. Large-scale benchmark tests show that the new hybrid COFACTOR approach significantly improves the function annotation accuracy of the former structure-based pipeline and other state-of-the-art functional annotation methods, particularly for targets that have no close homology templates. The updated COFACTOR server and the template libraries are available at http://zhanglab.ccmb.med.umich.edu/COFACTOR/.
384 citations
Cites methods from "XSEDE: Accelerating Scientific Disc..."
...Part of the method training and benchmarking work was done on the Extreme Science and Engineering Discovery Environment (XSEDE) (40) and the Open Science Grid....
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References
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Proceedings Article•
Argonne National Laboratory1, University of California, San Diego2, University of Illinois at Urbana–Champaign3, California Institute of Technology4, Purdue University5, University of North Carolina at Chapel Hill6, Clemson University7, Oak Ridge National Laboratory8, University of Wisconsin-Madison9, Indiana University10, Indiana University – Purdue University Indianapolis11, University of Pittsburgh12, Northern Illinois University13, University of Southern California14, Cornell University15, National Center for Atmospheric Research16, Microsoft17, Sun Microsystems18, University of Michigan19
TL;DR: The TeraGrid project has been supported through a variety of funding and in-kind con- tributions in addition to multiple grants from the National Science Foundation.
Abstract: The TeraGrid project has been supported through a variety of funding and in-kind con- tributions in addition to multiple grants from the National Science Foundation. State support has come from the states of California, Illinois, Indiana, Pennsylvania, and Texas. Institutional support has come from Carnegie Melon University, Indiana Uni- versity, Purdue University, University of California-San Diego, University of Chicago, University of Illinois at Urbana-Champaign, University of Pittsburgh, the University of North Carolina, California Institute of Technology, and the University of Texas. Cor- porate support has come from Cray, Dell, IBM, Lilly Endowment, Qwest Communica- tions, and Sun Microsystems. Several hundred staff members from partner institutions contribute to the TeraGrid facility.
186 citations