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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://ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23, 2019.BGMUT was database that provided publicly accessible platform for DNA sequences and curated set of blood mutation information. Data Archive are available at ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive.
Proper citation: Blood Group Antigen Gene Mutation Database (RRID:SCR_002297) Copy
A question answer forum for scientists, focusing on methods in bioinformatics, computational genomics and biological data analysis. They welcome detailed and specific posts, written clearly and simply.
Proper citation: BioStar (RRID:SCR_002580) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, Documented on March 24, 2014. A resource for gene expression studies, storing highly curated MIAME-compliant studies (i.e. experiments) employing a variety of technologies such as filter arrays, 2-channel microarrays, Affymetrix chips, SAGE, MPSS and RT-PCR. Data were available for querying and downloading based on the MGED ontology, publications or genes. Both public and private studies (the latter viewable only by users having appropriate logins and permissions) were available from this website. Specific details on protocols, biomaterials, study designs, etc., are collected through a user-friendly suite of web annotation forms. Software has been developed to generate MAGE-ML documents to enable easy export of studies stored in RAD to any other database accepting data in this format. RAD is part of a more general Genomics Unified Schema (http://gusdb.org), which includes a richly annotated gene index (http://allgenes.org), thus providing a platform that integrates genomic and transcriptomic data from multiple organisms. NOTE: Due to changes in technology and funding, the RAD website is no longer available. RAD as a schema is still very much active and incorporated in the GUS (Genomics Unified Schema) database system used by CBIL (EuPathDB, Beta Cell Genomics) and others. The schema for RAD can be viewed along with the other GUS namespaces through our Schema Browser.
Proper citation: RNA Abundance Database (RRID:SCR_002771) Copy
Project to provide Neuroscience Community with mouse strains that are suitable for tissue and cell-type-specific perturbation of gene function in nervous system. NIH Neuroscience Blueprint has established three centers in the USA for generation of genetically modified mice expressing CRE recombinases in nervous system on the C57BJ/6 genetic background. Mouse lines are generated at Cold Spring Harbor Lab, at Scripps Research Institute, and at Baylor College of Medicine.
Proper citation: CRE Driver Network (RRID:SCR_002720) Copy
http://www.mybiosoftware.com/population-genetics/332
A tool for SNP Search and downloading with local management. It also offers flanking sequence downloading and automatic SNP filtering. It requires Windows and .NET Framework.
Proper citation: SNPHunter (RRID:SCR_002968) Copy
http://insitu.fruitfly.org/cgi-bin/ex/insitu.pl
Database of embryonic expression patterns using a high throughput RNA in situ hybridization of the protein-coding genes identified in the Drosophila melanogaster genome with images and controlled vocabulary annotations. At the end of production pipeline gene expression patterns are documented by taking a large number of digital images of individual embryos. The quality and identity of the captured image data are verified by independently derived microarray time-course analysis of gene expression using Affymetrix GeneChip technology. Gene expression patterns are annotated with controlled vocabulary for developmental anatomy of Drosophila embryogenesis. Image, microarray and annotation data are stored in a modified version of Gene Ontology database and the entire dataset is available on the web in browsable and searchable form or MySQL dump can be downloaded. So far, they have examined expression of 7507 genes and documented them with 111184 digital photographs.
Proper citation: Patterns of Gene Expression in Drosophila Embryogenesis (RRID:SCR_002868) Copy
This resource provides a list of federal program officials in the neurosciences. An informal compendium of names and contact information for nearly 300 research grant and scientific review administrators in 21 organizational units.
Proper citation: NRF Contacts (RRID:SCR_001473) Copy
http://www.nesys.uio.no/Atlas3D/
A multi-platform visualization tool which allows import and visualization of 3-D atlas structures in combination with tomographic and histological image data. The tool allows visualization and analysis of the reconstructed atlas framework, surface modeling and rotation of selected structures, user-defined slicing at any chosen angle, and import of data produced by the user for merging with the atlas framework. Tomographic image data in NIfTI (Neuroimaging Informatics Technology Initiative) file format, VRML and PNG files can be imported and visualized within the atlas framework. XYZ coordinate lists are also supported. Atlases that are available with the tool include mouse brain structures (3-D reconstructed from The Mouse Brain in Stereotaxic Coordinates by Paxinos and Franklin (2001)) and rat brain structures (3-D reconstructed from The Rat Brain in Stereotaxic Coordinates by Paxinos and Watson (2005)). Experimental data can be imported in Atlas3D and warped to atlas space, using manual linear registration, with the possibility to scale, rotate, and position the imported data. This facilitates assignment of location and comparative analysis of signal location in tomographic images.
Proper citation: Atlas3D (RRID:SCR_001808) Copy
http://www.neuralgate.org/download/NeuralAct
Software to visualize electrocorticographic (ECoG) and possibly also other kinds of neural activity (EEG / EMG/ DOT) on a 3D model of the cortical surface. The tool has been used to produce cortical activation images and image sequences in several recent studies using ECoG. The tool is written in matlab. The package is thoroughly documented and includes a demo.
Proper citation: NeuralAct (RRID:SCR_002066) Copy
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
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
Ratings or validation data are available for this resource
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
http://www.patternlabforproteomics.org/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented July 5, 2018. Gene Ontology Explorer (GOEx) combines data from protein fold changes with GO over-representation statistics to help draw conclusions in proteomic experiments. It is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. A recent hack included in GOEx is to load the sparse matrix index file directly into GOEx, instead of going through the report generation using the AC/T-fold methods. This makes it easy for GOEx to analyze any list of proteins as long as the list follows the index file format (described in manuscript) . Please note that if using this alternative strategy, there will be no protein fold information. Platform: Windows compatible
Proper citation: GOEx - Gene Ontology Explorer (RRID:SCR_005779) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. Project to advance understanding of the neural mechanisms of vocal learning by providing a quantitative description of the relationship between physiological variables and vocal performance over the course of development in a songbird, the zebra finch. They propose to study vocal learning dynamically across neuronal and peripheral subsystems, using a novel collaborative approach that will harness the combined expertise of several investigators. Their proposed research model will 1) provide simultaneous measurements of acoustic, articulatory and electrophysiological data that will document the detailed dynamics of the vocal imitation process in a standardized learning paradigm; and 2) incorporate these measurements into a theoretical/computational framework that simultaneously provides a phenomenological description and attempts to elucidate the mechanistic basis of the learning process.
Proper citation: Zebra Finch Song Learning Consortium (RRID:SCR_006356) Copy
http://www.ebi.ac.uk/pdbe/emdb/
Repository for electron microscopy density maps of macromolecular complexes and subcellular structures at Protein Data Bank in Europe. Covers techniques, including single-particle analysis, electron tomography, and electron (2D) crystallography.
Proper citation: Electron Microscopy Data Bank at PDBe (MSD-EBI) (RRID:SCR_006506) Copy
http://grants.nih.gov/grants/oer.htm
OER serves as a vital interface between the NIH and the biomedical research community by guiding investigators through the process of attaining grants funding and helping them understand and navigate through federal policies and procedures. OER supports extramural research by providing policy and guidance to the 24 NIH Institutes and Centers that award grants. Extramural grants account for approximately 84 percent of NIH''s 29 billion budget. These are awarded to investigators throughout the U.S. and abroad. Approximately 10 percent of the NIH budget supports NIH intramural investigators, NIH staff who conduct research.
Proper citation: Office of Extramural Research NIH (RRID:SCR_006547) Copy
http://www.medschool.lsuhsc.edu/neuroscience/
Research center that takes multidisciplinary approach to neuroscience education and research. Research programs on molecular and cellular bases of neural diseases are the center of the innovative educational programs. Primary mission is to foster and conduct science that advances understanding of brain function and diseases that affect nervous system.
Proper citation: Louisiana State University School of Medicine Neurosciences Center (RRID:SCR_006446) Copy
http://www.ncbi.nlm.nih.gov/projects/genome/assembly/grc/
Consortium that puts sequences into a chromosome context and provides the best possible reference assembly for human, mouse, and zebrafish via FTP. Tools to facilitate the curation of genome assemblies based on the sequence overlaps of long, high quality sequences.
Proper citation: Genome Reference Consortium (RRID:SCR_006553) Copy
http://ciliate.org/index.php/home/welcome
TGD Wiki is a user-updatable database of information about the Tetrahymena thermophila genome sequence determined at The Institute for Genomic Research (TIGR). TGD Wiki provides information on the genome, genes, and proteins of Tetrahymena collected from the scientific literature, research community and many other resources. In order to keep the information in our database as current as possible, we will soon be inviting the members of the Tetrahymena community to add and update these annotations to reflect published research. TGD Wiki currently offers the following features: * Free, unrestricted read access to all available data * Sequence and annotation data for 24,725 genes (TIGR v.2008) * GBrowse genome browser with links to and from each gene page (TIGR v.2006) * BLAST searching of the TIGR gene models and genome sequence (TIGR v.2006) Tetrahymena Genome Database (TGD) Wiki began in 2004 at Stanford University using the schema and programs of its parent project, Saccharomyces Genome Database. TGD Wiki is now a collaboration between Bradley University, Stanford University, and Cornell University. As we begin TGD Wiki at its new home at Bradley University, the TGD Wiki database contains the following data from TGD: * Gene Names and Aliases * Gene Descriptions * Gene Ontology (GO) Annotations * Homologs (similar genes in selected organisms) * Protein Domains * Associated Literature * Paragraphs (longer, free-text descriptions of gene function, structure, and significance) * Coding and Protein Sequences We have updated the following fields to match the newest gene model sequences (TIGR v.2008): Coding and Protein Sequences, Protein Domains and Gene Descriptions. We will also be recalculating the GO Annotations (IEA evidence code) and Homologs as part of our effort to keep the annotations in TGD Wiki as current as possible. We will be relying on members of the Tetrahymena community to maintain high-quality, updated annotations in the remainder of the fields using our annotation interface. Also setting up new database superdb - for unpublished data Look at Ciliate.org for news on this and other new databases
Proper citation: TGD (RRID:SCR_012803) Copy
http://www.rcsb.org/#Category-welcome
Collection of structural data of biological macromolecules. Database of information about 3D structures of large biological molecules, including proteins and nucleic acids. Users can perform queries on data and analyze and visualize results.
Proper citation: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) (RRID:SCR_012820) Copy
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