The Neuroscience domain stands out from the field of sciences for its dependence on the study and characterization of complex, intertwining structures. Understanding the complexity of the brain has led to widespread advances in the structure of large-scale computing resources and the design of artificially intelligent analysis systems. However, the scale of problems and data generated continues to grow and outpace the standards and practices of neuroscience. In this paper, we present an automated neuroscience reconstruction framework, called NeuroKube, for large-scale processing and labeling of neuroimage volumes. Automated labels are generated through a machine-learning (ML) workflow, with data-intensive steps feeding through multiple GPU stages and distributed data locations leveraging autoscalable cloud-native deployments on a multi-institution Kubernetes system. Leading-edge hardware and storage empower multiple stages of machine-learning, GPU-accelerated solutions. This demonstrates an abstract approach to allocating the resources and algorithms needed to elucidate the highly complex structures of the brain. We summarize an integrated gateway architecture, and a scalable workflow-driven segmentation and reconstruction environment that brings together image big data with state-of-the-art, extensible machine learning methods.

SUMMARY: To expedite the review of semi-automated probability maps of organelles and other features from 3D electron microscopy data we have developed Probability Map Viewer, a Java-based web application that enables the computation and visualization of probability map generation results in near real-time as the data are being collected from the microscope. Probability Map Viewer allows the user to select one or more voxel classifiers, apply them on a sub-region of an active collection, and visualize the results as overlays on the raw data via any web browser using a personal computer or mobile device. Thus, Probability Map Viewer accelerates and informs the image analysis workflow by providing a tool for experimenting with and optimizing dataset-specific segmentation strategies during imaging. AVAILABILITY AND IMPLEMENTATION: https://github.com/crbs/probabilitymapviewer. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

We demonstrate an oral scientific simulation and its visualization based on E-science. This oral scientific application will become an essential key component for medical and dental clinic in the near future because Bio-Medical simulations will provide a clinical index considering a prognostic of a disease. In this case, it was shown that the physical theory of sound production of speech sound, sibilant. However, it is difficult to acquire the computational and storage resources in the hospitals. Our E-science infrastructure enables scientists and clinicians to achieve the advanced information produced by simulations. As the result of this phase implementation for Bio-Medical simulation on E-science infrastructure, we could extract the scientific findings about the oral science. Moreover, this infrastructure can be used more generally because of the divided architecture between applications and E-science infrastructure.

The Telescience Project/spl trade/ (https://telescience.ucsd.edu) aims to provide a complete, end-to-end, single sign-on solution for biomedical image analysis and structure-function correlation. Telescience merges advanced solutions for remote instrumentation (via Telemicroscopy/spl trade/), distributed data computation and storage, and transparent access to federated databases of cell structure. Here, we describe the Grid-based system architecture that enables the Telescience Project. This Grid service architecture provides a fabric for seamless interoperability among user interfaces (Web portals and applications) and externally addressable Grid resources (instruments and computers). Although many software components and tools provide some capabilities relating to enabling usable scientific grids, few systems offer the required complete interactions with grid infrastructures "out of the box". Significant time and effort, therefore, are needed for software evaluation, testing, and integration. Here we describe an emerging layer of the overall Grid infrastructure that provides a complete solution for application and portal developers to interact with core Grid functionality.

The Cybermedia Center, Osaka University (CMC) is a research institution that offers resource with knowledge and technology of all advanced research in the area of large-scale computation, information and communication, multimedia content and education. Currently, CMC involves in Japanese national grid projects such as JGN II (Japan Gigabit Network) and BioGrid. Not limited to Japan, CMC also takes an active part in international activities such as PRAGMA. In these projects and international collaboration, CMC has developed the Grid system that allows scientists to perform their analysis by remotely controlling the world-largest ultra-high voltage electron microscope located in Osaka University. On the other, CMC has been taking a leading role at BioGrid sharing experience and knowledge on the system development for biology. In this paper, we will describe BioGrid project overview and introduce progress of Telescience group which collaborates with Telescience project lead by National Center for Microscopy and Imaging Research (NCMIR).

For over the last decade, researchers at the National Center for Microscopy and Imaging Research (NCMIR, http://ncrrdr.ucsd.edu) have been developing and implementing novel technologies to propel collaborative research. NCMIR has built flexible high throughput, cyber infrastructure environments which connect researchers to advanced imaging instruments datagrids and computational grids. Through the integration of pioneering research in remote instrumentation research (known as Telemicroscopytrade) and grid based distributed computing and data management, this group demonstrated this vision in the context of The Telescience Project (https://telescience.ucsd.edu). Telescience provides an end-to-end, single sign-on solution for biomedical image analysis and structure-function correlation that integrates users with resources and applications with unified security and without prohibitive complexity. Here, we describe the flattening and generalization of the layers of software that make up the Grid-based system architecture of the project. In particular, we focus on the maturation and generalization of the architecture, including the development of an Application to middleware interaction component (ATOMIC) services fabric that streamlines application integration with core grid middleware. This broadening of the overall grid service architecture is the product of over 6 years of user-developer iterative software refinement cycles which have resulted in a suite of Telescience Tools that provide generalized solutions for increasing the interoperability of user interfaces (Web portals and applications) and externally addressable grid resources (instruments and computers)

Scientific imaging instruments are used in a variety of disciplines to gather vital data for research and study. Specifically, in the biomedical field various types of biological imaging instruments, such as electron microscopes and light microscopes, are used everyday to acquire 2D and 3D datasets for further understanding of biological structures. Remote operation or "teleoperation" of instruments has become a popular solution for research scientists to acquire and share data across research domains separated by geographical barriers. A generalized software architecture solution is presented in this paper to use emerging software technologies to develop a reusable framework to easily integrate instruments for remote-operation in a safe and secure fashion. Web services have emerged as a popular technology to provide software applications with a framework to achieve interoperability and integration with other applications. This generalized software architecture was developed to take advantage of Web service middleware technology and to provide a solution for easily plugging in scientific imaging instruments for teleoperation. The architecture has also incorporated grid technology to achieve a more scalable and robust solution for handling the enormous data sets produced from these instruments. Finally a set of client libraries is presented to demonstrate a useful API for developers to quickly develop a graphical user interface to communicate and acquire data from these instruments