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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://www.ccmp.ox.ac.uk/peakdeck
A peak-calling software program for DNAseI-seq data.
Proper citation: PeaKDEck (RRID:SCR_004268) Copy
http://www.broadband-forum.org/
The Broadband Forum is the central organization driving broadband wireline solutions and empowering converged packet networks worldwide to better meet the needs of vendors, service providers and their customers. They develop multi-service broadband packet networking specifications addressing interoperability, architecture and management. Their work enables home, business and converged broadband services, encompassing customer, access and backbone networks. Keywords: Vendor, Service, Broadband, Wireline, Forum, Network,
Proper citation: Broadband Forum (RRID:SCR_004260) Copy
http://www.creativebiomart.net/
An Antibody supplier
Proper citation: Creative Biomart (RRID:SCR_004255) Copy
https://github.com/alyssafrazee/derfinder
R package for differential expression analysis of RNA-seq data.
Proper citation: DER Finder (RRID:SCR_004250) Copy
http://www.bioconductor.org/packages/release/bioc/html/flowMap.html
Software package that quantifies the similarity of cell populations across multiple flow cytometry samples using a nonparametric multivariate statistical test. The algorithm allows the users to specify a reference sample for comparison or to construct a reference sample from the available data. The output of the algorithm is a set of text files where the cell population labels are replaced by a metaset of population labels, generated from the matching process.
Proper citation: flowMap (RRID:SCR_002269) Copy
http://rgp.dna.affrc.go.jp/E/index.html
Rice Genome Research Program (RGP) is an integral part of the Japanese Ministry of Agriculture, Forestry and Fisheries (MAFF) Genome Research Project. RGP now aims to completely sequence the entire rice genome and subsequently to pursue integrated goals in functional genomics, genome informatics and applied genomics. It is jointly coordinated by the National Institute of Agrobiological Sciences (NIAS), a government research institute under MAFF and the Society for Techno-innovation of Agriculture, Forestry and Fisheries (STAFF), a semi-private research organization managed and supported by MAFF and a consortium of some twenty Japanese companies. The research is funded with yearly grants from MAFF and additional funds from the Japan Racing Association (JRA). It is now the leading member of the International Rice Genome Sequencing Project (IRGSP), a consortium of ten countries sharing the sequencing of the 12 rice chromosomes. The IRGSP adopts the clone-by-clone shotgun sequencing strategy so that each sequenced clone can be associated with a specific position on the genetic map and adheres to the policy of immediate release of the sequence data to the public domain. In December 2004, the IRGSP completed the sequencing of the rice genome. The high-quality and map-based sequence of the entire genome is now available in public databases.
Proper citation: Rice Genome Research Project (RRID:SCR_002268) Copy
http://neuromorpho.org/index.jsp
Centrally curated inventory of digitally reconstructed neurons associated with peer-reviewed publications that contains some of the most complete axonal arborizations digitally available in the community. Each neuron is represented by a unique identifier, general information (metadata), the original and standardized ASCII files of the digital morphological reconstruction, and a set of morphometric features. It contains contributions from over 100 laboratories worldwide and is continuously updated as new morphological reconstructions are collected, published, and shared. Users may browse by species, brain region, cell type or lab name. Users can also download morphological reconstructions for research and analysis. Deposition and distribution of reconstruction files ultimately prevents data loss. Centralized curation and annotation aims at minimizing the effort required by data owners while ensuring a unified format. It also provides a one-stop entry point for all available reconstructions, thus maximizing data visibility and impact.
Proper citation: NeuroMorpho.Org (RRID:SCR_002145) Copy
http://www.pc.rhul.ac.uk/staff/J.Larsson/software.html
Set of programs and Tk/Tcl scripts, with a GUI wrapper, for extracting the inner and outer cortical surfaces from a T1-weighted MR image of the human brain. It is based on the TFI C++ library and is written for a Unix-based environment (specifically 64-bit and 32-bit versions of Ubuntu). As a courtesy to Apple users a version for Apple/X11 is maintained but the OS X version will always lag the Linux version; also, because some of the third-party libraries SurfRelax relies on may not be supported in or compatible with future versions of OS X, there is no guarantee that the OS X version will be supported indefinitely. Although in principle SurfRelax could be run under Windows (using Cygwin), because of the difficulties of maintaining multiple platforms and the limited support libraries available under Cygwin, there will no longer be support for SurfRelax on this platform. The surfaces are guaranteed to be topologically equivalent to a sphere, thereby obviating the need for handle removal. SurfRelax requires no user intervention, although minor manual editing is recommended for optimal results (normally less than 10 minutes per hemisphere). SurfRelax has several properties that compare favorably with other software packages for surface reconstruction: * Free software - The binaries (written in C++ and Tcl/Tk) are in the public domain. The source code will be released once legacy code issues have been resolved (i.e. replacing with GPL code). * Uses standard public file formats: Analyze file format (SPM/FSL-compatible) for volumes and OOGL OFF binary format for surfaces (see www.geomview.org (http://www.geomview.org/docs/html/geomview_26.html#OOGLRef)) * Combines advantages of volumetric and surface-based methods for surface generation * Correct topology of output surface guaranteed * Requires little or no user intervention - no need for manual handle removal * Relatively robust to noise - multi-scale method compensates for partial volume effects and intensity inhomogeneities * Relatively fast (an entire brain is segmented, extracted and unfolded in less than 2 hours of CPU time) * Powerful editing and visualization tools for volumes and surfaces * Readily extendable - for instance for use with monkey brains or children's brains * Can be used to visualize functional data from SPM or FSL * Includes tools for integration with Stanford's VISTASOFT tools for FMRI data analysis (white.stanford.edu)
Proper citation: SurfRelax (RRID:SCR_002139) Copy
http://cakesomatic.sourceforge.net/
A bioinformatics software pipeline that integrates four publicly available somatic variant-calling algorithms to identify single nucleotide variants with higher sensitivity and accuracy than any one algorithm alone.
Proper citation: Cake (RRID:SCR_002133) Copy
http://www.comp-sys-bio.org/yeastnet/
This is a portal to the consensus yeast metabolic network as reconstructed from the genome sequence and literature. It is a highly annotated metabolic map that is periodically updated by a team of collaborators from various research groups. The first version of this reconstruction was published in Herrgrd, Swainston et al. (2008) A consensus yeast metabolic reconstruction obtained from a community approach to systems biology Nature Biotechnol. 26, 1155-1160 (you can access that network here). A second version has now been released and is awaiting publication. We plan on continuing to update this resource towards a complete metabolic network of yeast. All versions will remain accessible for historical purposes, however it is highly recommended that you always use the latest one since that is the most up to date. This effort started on the shoulders of a number of reconstructions of the metabolic network of yeast based on genomic and literature data that were published separately. (iMM904 and iLL672) However, due to the different approaches utilized in them, those earlier reconstructions had a significant number of differences. In addition they suffered from the use of non-standard names and overall they were not annotated with methods that are machine-readable. A community effort in 2007, led by the Manchester Centre for Integrative Systems Biology and the YSBN resulted in a consensus network representation of yeast metabolism, reconciling the earlier results. That effort is now ongoing under the leadership of the MCISB and with collaboration with colleagues under the UNICELLSYS FP7 project. Availability The network reconstruction is primarily assembled and provided as an SBML file enriched with MIRIAM-compliant annotations (which are embedded in the SBML through RDF). All small and macro- molecules are referenced to an authoritative database (e.g. Uniprot, ChEBI, etc.). All molecules and reactions are also annotated with appropriate publications that contain supporting evidence. Thus this network is entirely traceable and is presented in a computational framework. SBML is a format that is understood by a large number of software applications (see sbml.org). While the SBML file is the most efficient computational resource for these data, casual users also need access to the network. That is provided by a searchable relational database accessed directly from this website. The database pages also allow readers to add comments to any chemical species or reaction. Such comments are taken into consideration by the team collating new versions of the network and can lead to corrections and additions to the network. This reconstruction is provided in the following formats: :* an SBML file containing the reaction network and annotations, located to specific sub-cellular compartments :* an SBML file containing the reaction network and annotations without subcellular compartmentation (all reactions happening in a single compartment). :* a searcheable relational database, which uses the B-Net software from Pedro Mendes' group. The database version of this data set is managed with the B-Net software created in Pedro Mendes' group at the Virginia Bioinformatics Institute. B-Net's schema is a detailed representation of the underlying biochemistry and regulation. A number of reconstructions of the metabolic network of yeast based on genomic and literature data have been published. However, due to different approaches utilized in the reconstruction as well as different interpretations of the literature, the earlier reconstructions have significant number of differences. A community effort resulted in a consensus network model of yeast metabolism, combining results from previous models.
Proper citation: Yeast consensus metabolic network - A consensus reconstruction of yeast metabolism (RRID:SCR_002135) Copy
https://scicrunch.org/resolver/SCR_002250
THIS RESOURCE IS NO LONGER IN SERVICE. Documented Jul 19, 2024. Metadatabase manually curated that provides web accessible tools related to genomics, transcriptomics, proteomics and metabolomics. Used as informative directory for multi-omic data analysis.
Proper citation: OMICtools (RRID:SCR_002250) Copy
http://www.broadinstitute.org/mpg/snap/
A computer program and web-based service for the rapid retrieval of linkage disequilibrium proxy single nucleotide polymorphism (SNP) results given input of one or more query SNPs and based on empirical observations from the International HapMap Project and the 1000 Genomes Project. A series of filters allow users to optionally retrieve results that are limited to specific combinations of genotyping platforms, above specified pairwise r2 thresholds, or up to a maximum distance between query and proxy SNPs. SNAP can also generate linkage disequilibrium plots
Proper citation: SNAP - SNP Annotation and Proxy Search (RRID:SCR_002127) Copy
Repository providing free access to marine geophysical data (e.g. bathymetry, seismic data, magnetics, gravity, images) and related land-based data from NSF-funded research conducted throughout the global oceans. Data Portals include GeoPRISMS, MARGINS, Ridge 2000, Antarctic and Southern Ocean Data Synthesis, the Global Multi-Resolution Topography Synthesis, and Seismic Reflection Field Data Portal. Primary data types served are multibeam bathymetric data from the ocean floor, seismic reflection data imaging below the seafloor, and multi-disciplinary ship based data from the Southern Ocean. Other holdings include deep-sea photographic transects, and ultra-high resolution bathymetry, temperature probe data, biological species compilations, MAPR and CTD data. Derived data products and sets include microseismicity catalogs, images, visualization scenes, magnetic and gravity compilations, grids of seismic layer thickness, velocity models, GIS project files, and 3D visualizations. Tools to discover, explore, and visualize data are available. They deliver catalogs, maps, and data through standard programmatic interfaces. GeoMapApp, a standalone data visualization and analysis tool, permits dynamic data exploration from a map interface and the capability to generate and download custom grids and maps and other data. Through GeoMapApp, users can access data hosted at the MGDS, at other data repositories, and import their own data sets. Global Multi-Resolution Topography (GMRT) is a continuously-updated compilation of seafloor bathymetry integrated with global land topography. It can be used to create maps and grids and it can be accessed through several standard programmatic interfaces including GeoMapApp and Google Earth. The GMRT compilation can also be explored in 3D using Virtual Ocean. The MGDS MediaBank contains high quality images, illustrations, animations and video clips that are organized into galleries. Media can be sorted by category, and keyword and map-based search options are provided. Each item in the MediaBank is accompanied by metadata that provides access to a cruise catalog and data repository.
Proper citation: Marine Geoscience Data System (RRID:SCR_002164) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented June 5, 2017. It has been merged with Cell Image Library. Database for sharing and mining cellular and subcellular high resolution 2D, 3D and 4D data from light and electron microscopy, including correlated imaging that makes unique and valuable datasets available to the scientific community for visualization, reuse and reanalysis. Techniques range from wide field mosaics taken with multiphoton microscopy to 3D reconstructions of cellular ultrastructure using electron tomography. Contributions from the community are welcome. The CCDB was designed around the process of reconstruction from 2D micrographs, capturing key steps in the process from experiment to analysis. The CCDB refers to the set of images taken from microscope the as the Microscopy Product. The microscopy product refers to a set of related 2D images taken by light (epifluorescence, transmitted light, confocal or multiphoton) or electron microscopy (conventional or high voltage transmission electron microscopy). These image sets may comprise a tilt series, optical section series, through focus series, serial sections, mosaics, time series or a set of survey sections taken in a single microscopy session that are not related in any systematic way. A given set of data may be more than one product, for example, it is possible for a set of images to be both a mosaic and a tilt series. The Microscopy Product ID serves as the accession number for the CCDB. All microscopy products must belong to a project and be stored along with key specimen preparation details. Each project receives a unique Project ID that groups together related microscopy products. Many of the datasets come from published literature, but publication is not a prerequisite for inclusion in the CCDB. Any datasets that are of high quality and interest to the scientific community can be included in the CCDB.
Proper citation: Cell Centered Database (RRID:SCR_002168) Copy
Search engine integrating various bio-informatic resources and algorithims to produce a one-stop resource for biologists to identify potentially functional SNPs. It caters to different groups of scientists interested in SNPs including those working in the following areas: * Whole-genome association studies * Gene-based association studies * Designing experiments to address the functionality of specific SNPs * Determining potentially functionally significant SNPs that are in LD with non-pfSNPs of interest. Users may add published SNP functions.
Proper citation: pfSNP (RRID:SCR_002167) Copy
http://www.bioconductor.org/packages/release/bioc/html/flowMatch.html
Software for matching cell populations and building meta-clusters and templates from a collection of flow cytometry (FC) samples.
Proper citation: flowMatch (RRID:SCR_002283) Copy
Independent international facilitator catalyzing and coordinating global development of neuroinformatics aiming to advance data reuse and reproducibility in global brain research. Integrates and analyzes diverse data across scales, techniques, and species to understand brain function and positively impact the health and well being of society.
Proper citation: International Neuroinformatics Coordinating Facility (RRID:SCR_002282) Copy
http://www.bioconductor.org/packages/release/bioc/html/flowMeans.html
Software that identifies cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection.
Proper citation: flowMeans (RRID:SCR_002275) Copy
https://CRAN.R-project.org/package=rmeta
Package of software functions for simple fixed and random effects meta-analysis for two-sample comparisons and cumulative meta-analyses. Draws standard summary plots, funnel plots, and computes summaries and tests for association and heterogeneity.
Proper citation: rmeta (RRID:SCR_002270) Copy
National data center / repository for snow and ice data including snow, ice, glaciers, frozen ground, and climate interactions that make up Earth's cryosphere. The center manages and distributes scientific data, creates tools for data access, supports data users, performs scientific research, and educates the public about the cryosphere. Users may explore the Earth's frozen places in the collection of photographs and images. Photographs from field research trips, images captured by satellites of the changing cryosphere, and photos and images are available. Data sets are organized into the following groups: sea ice, frozen ground, snow cover, snow hydrology, glaciers and ice sheets, arctic people.
Proper citation: National Snow and Ice Data Center (RRID:SCR_002220) Copy
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