Curator Dashboard

Software that allows large scale neuron simulators to communicate during runtime. It allows exchange of data among parallel applications in a cluster environment, interconnects large-scale neuronal network simulators with each other or with other tools, participates in multi-simulations, and is continuously developed and extended. Three simulators currently have MUSIC interfaces: Moose, NEURON and NEST. Three applications execute in parallel while exchanging data via MUSIC. The software interface promotes interoperability by allowing models written for different simulators to be simulated together in a larger system. It enables re-usability of models or tools by providing a standard interface. As data are distributed over a number of processors, it is non-trivial to coordinate data transfer so that it reaches the correct destination at the correct time. Current and future simulators can make use of MUSIC - compliant general purpose tools and participate in multi-simulations, for example when: * Different parts of a complex nervous system model are optimally implemented in different simulators, and need to communicate with each other. * Post-processing of generated data is needed, where the amounts of data are too large for intermediate storage, and requires the simulator to pass the data directly to the post-processing module. A standard interface enables straight-forward independent third-party development and community sharing of interoperable software tools for parallel processing. * Library and utilities are written in C++, uses MPI. * It is possible to add a MUSIC interface to existing simulators. * Works independently, no assumptions are made about other applications to facilitate development of general purpose tools. * Performance Data transport with high bandwidth and low latency.

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• SciCrunch
• 17 years ago - by Anonymous

Through this site, INCF provides he neuroinformatics community with access to an IBM Blue Gene/L supercomputer. INCF owns a share of a BlueGene/L (BG/L) supercomputer located at the Parallel Computer Center (PDC) at The Royal Institute of Technology (KTH) in Stockholm. Allocations are now available through the INCF Secretariat. During an initial evaluation phase, a limited numbers of large-scale computing projects will be selected, based on the suitability of the project for supercomputing. Research groups with limited access to supercomputers at their home institutions are given priority. Approved projects are regularly re-evaluated. New projects are approved based on availability and usage load of the BG/L. The Blue Gene/L supercomputer project is aimed at expanding the horizon of high-performance computing to unprecedented levels of scale and performance. Blue Gene/L is the first supercomputer in the Blue Gene family. The full Blue Gene/L consists of 64 racks containing 65,536 high-performance compute nodes. Each node (nodes and chips are the same in the Blue Gene system) contains two embedded 32-bit PowerPC processors. Furthermore, the same chip that is used for compute nodes is also used for the 1,024 I/O nodes. A three-dimensional torus network and a collective network are used to interconnect all nodes. The full system contains 33 terabytes of main memory; it is designed to achieve 183.5 teraflops peak performance using one of the processors of each node for computation and the other processor for communication, and 367 teraflops using both processors for computation. Another key architectural feature of this supercomputer is the link chip component and five Blue Gene/L networks, the PowerPC 440 core and floating-point enhancements, the on-chip and off-chip distributed memory system, the node- and system-level design for high reliability, and the comprehensive approach to fault isolation. One of the key objectives in Blue Gene/L design is to achieve cost/performance comparable to the COTS (Commodity Off The Shelf) approach, while at the same time incorporating a processor and network combination so powerful that it revolutionizes the performance of supercomputer systems. Sponsors: This resource is supported by the INCF.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19. 2022. Platform to promote studies on dynamic principles of brain functions through unifying experimental and computational approaches in cellular, local circuit, global network and behavioral levels. Provides services such as data sets, popular research findings and articles and current developments in field. This site has been archived since FY2019 and is no longer updated.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. AOBase is a database for antisense oligonucleotides (AOs) selection and design. AOBase is a database developed to facilitate Antisense Oligonucleotides (ODNs) selection for gene expression modulation and to provide a free data source for computer aided ODNs design. Information about valid and invalid ODNs reported in literature are collected and stored in the database, including oligo sequences, target sequences, secondary structures of the target sites, oligo activity measured, and the assay type used for activity measurement. The details on target RNA molecules and reference literature can be explored through the hyperlinks linked to GenBank and PubMed respectively. Each record can be searched for via two web retrieval interfaces: 1) TargetSearch interface, which allows users to query ODNs by name, accession number, or only imprecise descriptions of its target RNA; 2) AOSearch interface, which allows users to search ODNs with several parameters combined, such as oligo activity measured, oligo concentration applied, and motifs involved in oligo sequences. With these two retrieval interfaces, AOBase can be used to select effective ODNs for gene function exploration without expensive in vitro screening experiments, and contribute to mining rules for rational ODNs design. A user friendly interface to encourage data submission is provided.

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• SciCrunch
• 17 years ago - by Anonymous

Online portal and image database of coronal sections of the sheep brain. Each image contains stained sections of cell bodies and myelinated fibers; nuclei and tracts are labeled.

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• SciCrunch
• 14 years ago - by Anonymous

This resouce will centralize development of tools for interaction with medical imaging data in immersive virtual environments (based on the Vizard platform).

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• SciCrunch
• 13 years ago - by Anonymous

Database with quantitative binding data for peptides binding to various cells including MHC Ligand, TCR-MHC complexes, T-cell epitopes, TAP, B-cell, and immunological protein-protein interactions. Information in each entry includes peptide libraries, copy numbers, and diffusion coefficient data.

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• SciCrunch
• 16 years ago - by Anonymous

Data management software that runs the Pathway Commons web service. It makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Main features: * Import pipeline capable of aggregating pathway and interaction data sets from multiple sources, including: MINT, IntAct, HPRD, DIP, BioCyc, KEGG, PUMA2 and Reactome. * Import/Export support for the Proteomics Standards Initiative Molecular Interaction (PSI-MI) and the Biological Pathways Exchange (BioPAX) XML formats. * Data visualization and analysis via Cytoscape. * Simple HTTP URL based XML web service. * Complete software is freely available for local install. Easy to install and administer. * Partly funded by the U.S. National Cancer Institute, via the Cancer Biomedical Informatics Grid (caBIG) and aims to meet silver-level requirements for software interoperability and data exchange.

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• SciCrunch
• 13 years ago - by Anonymous

Database of trait mapping data, i.e. QTL (phenotype / expression, eQTL), candidate gene and association data (GWAS) and copy number variations (CNV) mapped to livestock animal genomes, to facilitate locating and comparing discoveries within and between species. New data and database tools are continually developed to align various trait mapping data to map-based genome features, such as annotated genes. QTLdb is open to house QTL/association date from other animal species where feasible. Most scientific journals require that any original QTL/association data be deposited into public databases before paper may be accepted for publication. User curator accounts are provided for direct data deposit. Users can download QTLdb data from each species or individual chromosome.

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• SciCrunch
• 13 years ago - by Anonymous

Online portal resource with hierarchically-organized list of links to web resources concerning neurological disorders.

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• SciCrunch
• 17 years ago - by Anonymous

A collection of omics datasets (mRNA, proteins and miRNA) that have been extracted from PubMed and other related renal databases, all related to kidney physiology and pathology giving KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. Some microarray raw datasets have also been downloaded from the Gene Expression Omnibus and analyzed by the open-source software GeneArmada. The Semantic Web technologies, together with the background knowledge from the domain's ontologies, allows both rapid conversion and integration of this knowledge base. SPARQL endpoint http://sparql.kupkb.org/sparql The KUPKB Network Explorer will help you visualize the relationships among molecules stored in the KUPKB. A simple spreadsheet template is available for users to submit data to the KUPKB. It aims to capture a minimal amount of information about the experiment and the observations made.

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• dkNET
• 13 years ago - by Anonymous

This portal leads to the Internet Atlas of Histology. This atlas allows you to explore the complete set of histological specimens that features many excellent plastic sections prepared by Aulikki Kokko-Cunningham, M.D. Also called University of Illnois at Urbana-Champaign, the College of Medicine: Internet Atlas of Histology Over 1000 labeled histological features are labeled and have accompanying functional descriptions. All of this information is accessible though an alphabetical index and a search engine. This resource has images categorized in: - Slides: Links to all of the specimens - Objects:Index of histological features Sponsors: This resource is supported by UIUC.

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• SciCrunch
• 17 years ago - by Anonymous

Public research university located in London, United Kingdom that offers undergraduate, graduate, and professional degree programs in medicine, economics, social sciences, etc.

• Organization
• SciCrunch
• 13 years ago - submitted by Christie Wang

Software that provides basic S4 data structures and routines for analyzing plate based flow cytometry data.

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• SciCrunch
• 12 years ago - by Anonymous

Online portal of the software resources provided by Hanchuan Peng's lab. Program functions include 3D image rendering, MATLAB toolboxs, image annotator, and cell explorer atlas and building tools.

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• SciCrunch
• 16 years ago - by Anonymous

The Krasnow Institute seeks to expand understanding of mind, brain, and intelligence by conducting research at the intersection of the separate fields of cognitive psychology, neurobiology, and the computer-driven study of artificial intelligence and complex adaptive systems. These separate disciplines increasingly overlap and promise progressively deeper insight into human thought processes. The Institute also examines how new insights from cognitive science research can be applied for human benefit in the areas of mental health, neurological disease, education, and computer design. It is this informed access to mind and brain that is the core of the mission of The Krasnow Institute. While their goals and tools are scientific, they also are fully cognizant of the applications of the results for the benefit of mankind, in areas like mental health, neurological diseases, and computer design. In asking the major questions they realized the necessity of being flexible, innovative, and trans-disciplinary. Therefore, they became dedicated to bringing together scholars from a wide variety of specialties and providing a milieu where they can be both productive and interactive. This institute will provide these researchers with the tools required to move ahead and create an environment of optimal scientific integrity coupling innovation with risk taking. The Krasnow institute is especially attuned to the deep insights from evolutionary biology, which is at the root of understanding all organismic functions including cognition; computer studies of complex systems, which present a revolution in our ability to deal with the world of interactive agents; and a long history of cognitive psychology, which provides a huge data base of human abilities and responses. It also continues to develop its long-term research program based on the contributions of George Mason University faculty holding joint appointments at Krasnow and other GMU academic departments. Additionally, the Krasnow Institute Department of Molecular Neuroscience, together with the College of Science (COS) and the College of Humanities and Social Sciences (CHSS), oversees the campus-wide Neuroscience Council in developing the Neuroscience PhD curriculum. Research groups in the Krasnow institute include: - Adaptive Systems Laboratory - Center for Neural Dynamics - Center for Social Complexity - Center for the Study of Neuroeconomics o Neuroeconomics Laboratory - Comparative Vertebrate Neurobiology Research Group - Center for Neuroinformatics, Neural Structures, and Neuroplasticity (CN3) o Computational and Experimental Neuroplasticity (CENlab) o Computational Neuroanatomy Group o Physiological and Behavioral Neuroscience in Juveniles (PBNJ) Lab - Receptor Complexes and Signaling Lab - Krasnow Investigations of Developmental Learning and Behavior (KIDLAB) - Neuro Imaging Core of the Krasnow Institute

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• SciCrunch
• 17 years ago - by Anonymous

Software for linkage and association modeling in pedigrees that uses a maximum likelihood model to extract information on genetic linkage and association from samples of unrelated individuals, sib pairs, trios and larger pedigrees (Li et al, 2005; Li et al, 2006). It provides estimates of genetic model parameters and powerful tests of association in settings where population stratification is not a concern.

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• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 10th,2023. An R software package for detecting and correcting biases in RNA-Sequencing data.

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• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 10th,2023. An R code for Bayesian modeling of paired RNA-seq experiments.

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• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Integrated database of experiment data generated by participating research institutes and public databases relating to: 1) transcription starting position of human genes in the human genome, 2) conjunction to control region on transcriptional factors and the human genome 3) protein-protein interaction with a central focus on transcription factors organized for use in genome level research. Gene Search is the function to search the integrated database by using keywords and public IDs. The search results can be visualized by: * Genome Explorer : provides annotation of landmarks (genes, transcription start sites, etc.) aligned in accordance with their genome locations. * PPI Network : provides a graphical view of protein-protein interaction (PPI) network from the experimental data generated under the project and the public datasets. * Expression Profile : clusters genes by expression pattern and display the result with heatmap. The function provides genes which have relation of coregulation and anti-coregulation. * Comparison Viewer : This function gives the view to compare the genomic regions between human and mouse homologous genes. The viewer shows the distribution of transcription start sites (TSS) as the way of separable by tissues or time points with other landmarks on genome region. * Gene Stock : This is the function to save the gene list that you are interested until the session is closed.

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• SciCrunch
• 17 years ago - by Anonymous