Tools   Select Another Resource Report Type

http://ligand-expo.rutgers.edu/

An integrated data resource for finding chemical and structural information about small molecules bound to proteins and nucleic acids within the structure entries of the Protein Data Bank. Tools are provided to search the PDB dictionary for chemical components, to identify structure entries containing particular small molecules, and to download the 3D structures of the small molecule components in the PDB entry. A sketch tool is also provided for building new chemical definitions from reported PDB chemical components.

Proper citation: Ligand Expo (RRID:SCR_006636) Copy   

•   Source: SciCrunch Registry

http://rice.plantbiology.msu.edu/

Database and resource that provides sequence and annotation data for the rice genome. This website provides genome sequence from the Nipponbare subspecies of rice and annotation of the 12 rice chromosomes. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 75 tracks of annotation. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads. Rice is a model species for the monocotyledonous plants and the cereals which are the greatest source of food for the world''s population. While rice genome sequence is available through multiple sequencing projects, high quality, uniform annotation is required in order for genome sequence data to be fully utilized by researchers. The existence of a common gene set and uniform annotation allows researchers within the rice community to work from a common resource so that their results can be more easily interpreted by other scientists. The objective of this project has always been to provide high quality annotation for the rice genome. They generated, refined and updated gene models for the estimated 40,000-60,000 total rice genes, provided standardized annotation for each model, linked each model to functional annotation including expression data, gene ontologies, and tagged lines. They have provided a resource to extend the annotation of the rice genome to other plant species by providing comparative alignments to other plant species. Analysis/Tools are available including: BLAST, Locus Name Search, Functional Term Search, Protein Domain Search, Anatomy Expression Viewer, Highly Expressed Genes

Proper citation: Rice Genome Annotation (RRID:SCR_006663) Copy   

•   Source: SciCrunch Registry

http://redfly.ccr.buffalo.edu

Curated collection of known Drosophila transcriptional cis-regulatory modules (CRMs) and transcription factor binding sites (TFBSs). Includes experimentally verified fly regulatory elements along with their DNA sequence, associated genes, and expression patterns they direct. Submission of experimentally verified cis-regulatory elements that are not included in REDfly database are welcome.

Proper citation: REDfly Regulatory Element Database for Drosophilia (RRID:SCR_006790) Copy   

•   Source: SciCrunch Registry

http://connectomes.utah.edu/

A web-compliant application that allows connectomics visualization by converting datasets to web-optimized tiles, delivering volume transforms to client devices, and providing groups of users with connectome annotation tools and data simultaneously via conventional internet connections. Viking is an extensible tool for connectomics analysis and is generalizable to histomics applications.

Proper citation: Viking Viewer for Connectomics (RRID:SCR_005986) Copy   

•   Source: SciCrunch Registry

http://www.crowdlabs.org/

A social visualization repository for the scientific workflow management system VisTrails providing a platform for sharing and executing computational tasks. It adopts the model used by social Web sites and that integrates a set of usable tools and a scalable infrastructure to provide an environment for scientists to collaboratively analyze and visualize data. crowdLabs aims to foster collaboration but was specifically designed to support the needs of computational scientists, including the ability to access high-performance computers and manipulate large volumes of data. By providing mechanisms that simplify the publishing and use of analysis pipelines, it allows IT personnel and end users to collaboratively construct and refine portals. This lowers the barriers for the use of scientific analyses and enables broader audiences to contribute insights to the scientific exploration process, without the high costs incurred by traditional portals. In addition, it supports a more dynamic environment where new exploratory analyses can be added on-the-fly.

Proper citation: crowdLabs (RRID:SCR_006294) Copy   

•   Source: SciCrunch Registry

http://evolution.genetics.washington.edu/phylip.html

A free package of software programs for inferring phylogenies (evolutionary trees). The source code is distributed (in C), and executables are also distributed. In particular, already-compiled executables are available for Windows (95/98/NT/2000/me/xp/Vista), Mac OS X, and Linux systems. Older executables are also available for Mac OS 8 or 9 systems.

Proper citation: PHYLIP (RRID:SCR_006244) Copy   

•   Source: SciCrunch Registry

http://cnas.ucr.edu/guppy/

A project that observes the processes of adaptive evolution in nature, and tests evolutionary hypotheses, by studying populations of guppies on the Caribbean island of Trinidad. Darwin thought that evolution by natural selection occurred very slowly, over hundreds if not thousands of years. Evolutionary biologists now know that evolutionary changes in species can happen very quickly, over a relatively few generations. The National Science Foundation (NSF), through its Integrative Biological Research (FIBR) program, is funding a 5-year study by 13 biologists from colleges, universities, and research institutions throughout the United States and Canada, to study the relationship of adaptive evolution and environmental circumstances. The Trinidadian guppy (Poecilia reticulata) is an excellent species for these purposes because: * It matures rapidly (one generation = 3-4 months) * It inhabits different ecological environments that can be easily manipulated On Trinidad, guppies live in streams, or portions of streams, that can differ in the species of predators that the guppies have to contend with. Some streams are high-predation environments, others low-predation. Different predation environments are often right next to one another, separated by a waterfall (which neither guppies nor predators can cross). Guppies from high-predation environments experience much higher mortality rates than do guppies in low-predation environments. High mortality is associated with the following characteristics, all of which have a genetic basis: * Earlier maturity * Greater investment of resources in reproduction * More and smaller offspring. We have found that mortality rates can be manipulated by: * Transplanting guppies from high-predation localities into sites from which they and their predators had previously been excluded by natural waterfalls, thus lowering mortality rates; * Introducing predators into low-predation sites, thus increasing mortality rates. Such experiments have shown that species evolve as predicted by theory. We have also found that evolution by natural selection can be remarkably fast, on the order of four to seven orders of magnitude faster than had been inferred from the fossil record.

Proper citation: Guppy Project (RRID:SCR_006255) Copy   

•   Source: SciCrunch Registry

http://great.stanford.edu/public/html/splash.php

Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool

Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy   

•   Source: SciCrunch Registry

http://umbbd.msi.umn.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms).

Proper citation: UM-BBD (RRID:SCR_005787) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.

Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy   

•   Source: SciCrunch Registry

http://pmgn.vbi.vt.edu

The Oomycete Molecular Genetics Research Collaboration Network (OMGN) is a network for research collaboration for investigators interested in oomycete molecular genetics and genomics. The goals of the OMGN is to facilitate the integration of these investigators into the community and to further strengthen the cooperative culture of this community. A particular emphasis is placed on training and integrating junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. Because of their economic impact as plant pathogens, molecular, genetic and genomics studies are well advanced in many oomycete species. These organisms have served as lead species for the entire Stramenopiles lineage, a major radiation of crown eukaryotes, distinct from plants, animals and fungi. The oomycete molecular genetics community has a strong culture of collaboration and communication, and sharing of techniques and resources. With the recent blossoming of genetic and genomic tools for oomycetes, many new investigators, from a variety of backgrounds, have become interested in oomycete molecular genetics and genomics. The proposed network is open to all researchers with an interest in oomycete molecular genetics and genomics, either at an experimental or a computational level. Investigators new to the field are always welcome, especially those interested in saprophytes and animal pathogens. Goals of OMGN # Provide training to o��mycete molecular genetics researchers, especially those from smaller institutions, in the use of bioinformatics and genomics resources. # Promote the entry, participation and training of new investigators into the field of o��mycete genomics, particularly junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. # Promote communication and collaboration, and minimize duplication of effort, within the worldwide o��mycete genomics community. # Support an O��mycete Genomics Resources Center to maintain and distribute training and research materials produced by community genomics projects. The network''s activities have been supported by two grants from the NSF Research Collaboration Networks in Biology program.

Proper citation: OMGN (RRID:SCR_005781) Copy   

•   Source: SciCrunch Registry

http://mcbc.usm.edu/gofetcher/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: Quick Search, Advanced Search, and Upload Files for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format. Platform: Online tool

Proper citation: GOfetcher (RRID:SCR_005681) Copy   

•   Source: SciCrunch Registry

http://icatb.sourceforge.net/fusion/fusion_startup.php

A MATLAB toolbox which implements the joint Independent Component Analysis (ICA), parallel ICA and CCA with joint ICA methods. It is used to to extract the shared information across modalities like fMRI, EEG, sMRI and SNP data. * Environment: Win32 (MS Windows), Gnome, KDE * Operating System: MacOS, Windows, Linux * Programming Language: MATLAB * Supported Data Format: ANALYZE, NIfTI-1

Proper citation: Fusion ICA Toolbox (RRID:SCR_003494) Copy   

•   Source: SciCrunch Registry

http://ccr.coriell.org/Sections/Collections/IPBIR/?SsId=18

The purpose of the IPBIR - Integrated Primate Biomaterials and Information Resource is to assemble, characterize, and distribute high-quality DNA samples of known provenance with accompanying demographic, geographic, and behavioral information in order to stimulate and facilitate research in primate genetic diversity and evolution, comparative genomics, and population genetics. Further research in these areas will advance our understanding of human origins, the biological basis of cognitive processes, evolutionary history and relationships, and social structure, and will provide critical scientific information needed to facilitate conservation of biological diversity. The derived DNA will be openly available to the broad scientific community who agree to restrict use to non-commercial purposes. DNA and cell culture samples are distributed only to qualified professional persons who are associated with recognized research, medical, or educational organizations engaged in research.

Proper citation: IPBIR - Integrated Primate Biomaterials and Information Resource (RRID:SCR_004614) Copy   

•   Source: SciCrunch Registry

http://datalad.org/

Project to adapt model of open source software distributions to address technical limitations of data sharing and develop all components of data distribution. Builds on top of git-annex and extends it with intuitive command line interface. Enables users to operate on data using familiar concepts, such as files and directories, while transparently managing data access and authorization with underlying hosting providers. Can create DataLad datasets using any data files published on the web.

Proper citation: DataLad (RRID:SCR_003931) Copy   

•   Source: SciCrunch Registry

http://www.delsaglobal.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 1, 2022. Organization whose mission is to build and promote a sustainable ecosystem of professional societies, funding agencies, foundations, companies, and citizens together with life science researchers and innovators in computing, infrastructure and analysis with the expressed goal of translating new discoveries into tools, resources and products.

Proper citation: DELSA (RRID:SCR_006231) Copy   

•   Source: SciCrunch Registry

https://www.msu.edu/~brains/brains/human/index.html

A labeled three-dimensional atlas of the human brain created from MRI images. In conjunction are presented anatomically labeled stained sections that correspond to the three-dimensional MRI images. The stained sections are from a different brain than the one which was scanned for the MRI images. Also available the major anatomical features of the human hypothalamus, axial sections stained for cell bodies or for nerve fibers, at six rostro-caudal levels of the human brain stem; images and Quicktime movies. The MRI subject was a 22-year-old adult male. Differing techniques used to study the anatomy of the human brain all have their advantages and disadvantages. Magnetic resonance imaging (MRI) allows for the three-dimensional viewing of the brain and structures, precise spatial relationships and some differentiation between types of tissue, however, the image resolution is somewhat limited. Stained sections, on the other hand, offer excellent resolution and the ability to see individual nuclei (cell stain) or fiber tracts (myelin stain), however, there are often spatial distortions inherent in the staining process. The nomenclature used is from Paxinos G, and Watson C. 1998. The Rat Brain in Stereotaxic Coordinates, 4th ed. Academic Press. San Diego, CA. 256 pp

Proper citation: Human Brain Atlas (RRID:SCR_006131) Copy   

•   Source: SciCrunch Registry

http://tulane.edu/som/regenmed/services/index.cfm

The Stem Cell Research and Regenerative Medicine''s Tissue Culture Core provides cells for research use within the department, as well as for distribution to other facilities. The core obtains hMSCs from bone marrow donor samples and expands these cells for research use. The hMSC''s are also characterized for bone, fat and cartilage differentiation, and are stored on site for use. The Tissue Culture Core also handles the expansion and characterization of mouse and rat MSC''s. The animal cells are cultured in a separate area, and never interact with human derived cells. We also have a supply of hMSC''s marked with GFP+, Mito Red and Mito Blue available.

Proper citation: Tulane Stem Cell Research and Regenerative Medicine Tissue Culture Core (RRID:SCR_007342) Copy   

•   Source: SciCrunch Registry

https://www.xsede.org/

XSEDE is a single virtual system that scientists can use to interactively share computing resources, data and expertise. People around the world use these resources and services things like supercomputers, collections of data and new tools to improve our planet. XSEDE resources may be broadly categorized as follows: High Performance Computing, High Throughput Computing, Visualization, Storage, and Data Services. Many resources provide overlapping functionality across categories. Scientists, engineers, social scientists, and humanists around the world - many of them at colleges and universities - use advanced digital resources and services every day. Things like supercomputers, collections of data, and new tools are critical to the success of those researchers, who use them to make our lives healthier, safer, and better. XSEDE integrates these resources and services, makes them easier to use, and helps more people use them. XSEDE supports 16 supercomputers and high-end visualization and data analysis resources across the country. Digital services, meanwhile, provide users with seamless integration to NSF''s high-performance computing and data resources. XSEDE''s integrated, comprehensive suite of advanced digital services will federate with other high-end facilities and with campus-based resources, serving as the foundation for a national cyberinfrastructure ecosystem. Common authentication and trust mechanisms, global namespace and filesystems, remote job submission and monitoring, and file transfer services are examples of XSEDE''s advanced digital services. XSEDE''s standards-based architecture allows open development for future digital services and enhancements. XSEDE also provides the expertise to ensure that researchers can make the most of the supercomputers and tools.

Proper citation: XSEDE - Extreme Science and Engineering Discovery Environment (RRID:SCR_006091) Copy   

•   Source: SciCrunch Registry

http://www.autopack.org/

A specialized version of autoPack designed to pack biological components together. The current version is optimized to pack molecules into cells with biologically relevant interactions to populate massive cell models with atomic or near-atomic details. Components of the algorithm pack transmembrane proteins and lipids into bilayers, globular molecules into compartments defined by the bilayers (or as exteriors), and fibrous components like microtubules, actin, and DNA.

Proper citation: Cellpack (RRID:SCR_006831) Copy   

•   Source: SciCrunch Registry