ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities. ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.

The Kepler Project is dedicated to furthering and supporting the capabilities, use, and awareness of the free and open source, scientific workflow application, Kepler. Kepler is designed to help scien­tists, analysts, and computer programmers create, execute, and share models and analyses across a broad range of scientific and engineering disciplines. Kepler can operate on data stored in a variety of formats, locally and over the internet, and is an effective environment for integrating disparate software components, such as merging "R" scripts with compiled "C" code, or facilitating remote, distributed execution of models. Using Kepler's graphical user interface, users simply select and then connect pertinent analytical components and data sources to create a "scientific workflow"-an executable representation of the steps required to generate results. The Kepler software helps users share and reuse data, workflows, and compo­nents developed by the scientific community to address common needs.

The world's largest set of data on human genetic variation - produced by the international 1000 Genomes Project - is now publicly available on the Amazon Web Services (AWS) cloud, the National Institutes of Health and AWS jointly announced today. The public-private collaboration demonstrates the kind of solutions that may emerge from the Big Data Research and Development Initiative announced today by the White House Office of Science and Technology Policy (OSTP) during an event at the American Association for the Advancement of Science in Washington, D.C.

The Defense Innovation Marketplace is a centralized online resource to better connect industry with government customers to invigorate innovation.

A large archive of medical images of cancer accessible for public download. Registering is free. All images are stored in DICOM file format. The images are organized as "Collections", typically patients related by a common disease (e.g. lung cancer), image modality (MRI, CT, etc) or research focus.

Driven by input from its scientific community, the Cancer Imaging Program (CIP) finds itself at the junction of two powerful scientific requisites; the need for cross-disciplinary research and inter-institutional data-sharing to speed scientific discovery and reduce redundancy, and the need to provide imaging phenotype data to augment large scale genomic analysis.

The NIH Human Connectome Project is an ambitious effort to map the neural pathways that underlie human brain function. The overarching purpose of the Project is to acquire and share data about the structural and functional connectivity of the human brain. It will greatly advance the capabilities for imaging and analyzing brain connections, resulting in improved sensitivity, resolution, and utility, thereby accelerating progress in the emerging field of human connectomics. Altogether, the Human Connectome Project will lead to major advances in our understanding of what makes us uniquely human and will set the stage for future studies of abnormal brain circuits in many neurological and psychiatric disorders.

Models of Infectious Disease Agent Study (MIDAS) is a collaboration of research and informatics groups to develop computational models of the interactions between infectious agents and their hosts, disease spread, prediction systems and response strategies. The models will be useful to policymakers, public health workers and other researchers who want to better understand and respond to emerging infectious diseases. If a disease outbreak occurs, the MIDAS network may be called upon to develop specific models to aid public officials in their decision-making processes. More information about MIDAS is available at the links below.

Keep informed about advances in structural biology and structural genomics. Discover how protein sequences, three-dimensional structures and models relate to biological function. Stay up to date with the latest protocols, materials and technologies.

In the past decade, there have been remarkable advances in proteomic technologies. Mass spectrometry has emerged as the preferred method for in-depth characterization of the protein components of biological systems. Using mass spectrometry, key insights into the composition, regulation and function of molecular complexes and pathways have been gained. From these studies, it is clear that mass-spectrometry-based proteomics is now a powerful 'hypothesis-generating engine' that, when combined with complementary molecular, cellular and pharmacological techniques, provides a framework for translating large data sets into an understanding of complex biological processes.

A new program package, XEASY, was written for interactive computer support of the analysis of NMR spectra for three-dimensional structure determination of biological macromolecules. XEASY was developed for work with 2D, 3D and 4D NMR data sets. It includes all the functions performed by the precursor program EASY, which was designed for the analysis of 2D NMR spectra, i.e., peak picking and support of sequence-specific resonance assignments, cross-peak assignments, cross-peak integration and rate constant determination for dynamic processes. Since the program utilizes the X-window system and the Motif widget set, it is portable on a wide range of UNIX workstations. The design objective was to provide maximal computer support for the analysis of spectra, while providing the user with complete control over the final resonance assignments. Technically important features of XEASY are the use and flexible visual display of lsquostripsrsquo, i.e., two-dimensional spectral regions that contain the relevant parts of 3D or 4D NMR spectra, automated sorting routines to narrow down the selection of strips that need to be interactively considered in a particular assignment step, a protocol of resonance assignments that can be used for reliable bookkeeping, independent of the assignment strategy used, and capabilities for proper treatment of spectral folding and efficient transfer of resonance assignments between spectra of different types and different dimensionality, including projected, reduced-dimensionality triple-resonance experiments.

A new program package, XEASY, was written for interactive computer support of the analysis of NMR spectra for three-dimensional structure determination of biological macromolecules. XEASY was developed for work with 2D, 3D and 4D NMR data sets. It includes all the functions performed by the precursor program EASY, which was designed for the analysis of 2D NMR spectra, i.e., peak picking and support of sequence-specific resonance assignments, cross-peak assignments, cross-peak integration and rate constant determination for dynamic processes. Since the program utilizes the X-window system and the Motif widget set, it is portable on a wide range of UNIX workstations. The design objective was to provide maximal computer support for the analysis of spectra, while providing the user with complete control over the final resonance assignments. Technically important features of XEASY are the use and flexible visual display of lsquostripsrsquo, i.e., two-dimensional spectral regions that contain the relevant parts of 3D or 4D NMR spectra, automated sorting routines to narrow down the selection of strips that need to be interactively considered in a particular assignment step, a protocol of resonance assignments that can be used for reliable bookkeeping, independent of the assignment strategy used, and capabilities for proper treatment of spectral folding and efficient transfer of resonance assignments between spectra of different types and different dimensionality, including projected, reduced-dimensionality triple-resonance experiments.

For the average biologist, hands-on literature mining currently means a keyword search in PubMed. However, methods for extracting biomedical facts from the scientific literature have improved considerably, and the associated tools will probably soon be used in many laboratories to automatically annotate and analyse the growing number of system-wide experimental data sets. Owing to the increasing body of text and the open-access policies of many journals, literature mining is also becoming useful for both hypothesis generation and biological discovery. However, the latter will require the integration of literature and high-throughput data, which should encourage close collaborations between biologists and computational linguists.

Comprehensive protein-protein interaction maps promise to reveal many aspects of the complex regulatory network underlying cellular function. Recently, large-scale approaches have predicted many new protein interactions in yeast. To measure their accuracy and potential as well as to identify biases, strengths and weaknesses, we compare the methods with each other and with a reference set of previously reported protein interactions.

GenMAPP is a free computer application designed to visualize gene expression and other genomic data on maps representing biological pathways and groupings of genes. Integrated with GenMAPP are programs to perform a global analysis of gene expression or genomic data in the context of hundreds of pathway MAPPs and thousands of Gene Ontology Terms (MAPPFinder), import lists of genes/proteins to build new MAPPs (MAPPBuilder), and export archives of MAPPs and expression/genomic data to the web.

Complex coupled multi-physics simulations are playing increasingly important roles in scientific and engineering applications such as fusion plasma and climate modeling. At the same time, extreme scales, high levels of concurrency and the advent of multicore and many core technologies are making the high-end parallel computing systems on which these simulations run, hard to program. While the Partitioned Global Address Space (PGAS) languages is attempting to address the problem, the PGAS model does not easily support the coupling of multiple application codes, which is necessary for the coupled multi-physics simulations. Furthermore, existing frameworks that support coupled simulations have been developed for fragmented programming models such as message passing, and are conceptually mismatched with the shared memory address space abstraction in the PGAS programming model. This paper explores how multi-physics coupled simulations can be supported within the PGAS programming framework. Specifically, in this paper, we present the design and implementation of the XpressSpace programming system, which enables efficient and productive development of coupled simulations across multiple independent PGAS Unified Parallel C (UPC) executables. XpressSpace provides the global-view style programming interface that is consistent with the memory model in UPC, and provides an efficient runtime system that can dynamically capture the data decomposition of global-view arrays and enable fast exchange of parallel data structures between coupled codes. In addition, XpressSpace provides the flexibility to define the coupling process in specification file that is independent of the program source codes. We evaluate the performance and scalability of Xpress Space prototype implementation using different coupling patterns extracted from real world multi-physics simulation scenarios, on the Jaguar Cray XT5 system of Oak Ridge National Laboratory.

VORPAL enables researchers to simulate complex physical phenomena in less time and at a much lower cost than empirically testing process changes for plasma and vapor deposition processes. VORPAL offers a unique combination of physical models to cover the entire range of plasma simulation problems. Ionization and neutral gas models enable VORPAL to bridge the gap between plasma and neutral flow physics. VORPAL software runs on a wide range of computing platforms, from desktop machines to massively parallel supercomputers with thousands of processors. The use of standard data formats allows data analysis at various levels of sophistication, including your own preferred data analysis tool. VORPAL is used by scientists and engineers to simulate the physical behavior of devices and processes for many industrial and research applications, including laser wakefield accelerators, plasma thrusters, high-power microwave guides, and plasma processing chambers.