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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://cerebrovascularportal.org
Portal enables browsing, searching, and analysis of human genetic information linked to cerebrovascular disease and related traits, while protecting the integrity and confidentiality of the underlying data.
Proper citation: Cerebrovascular Disease Knowledge Portal (RRID:SCR_015628) Copy
https://github.com/KravitzLab/fed/wiki
Flexible open-source device for measuring feeding behavior. FED measures food intake in mice. It is battery powered and designed to be used in rodent colony caging.Home cage-compatible feeding system that measures food intake with high accuracy and temporal resolution. FED offers alternative to commercial feeders, with convenience of use in tradition colony rack caging.
Proper citation: Feeding Experimentation Device project (RRID:SCR_015942) Copy
http://www.genetherapyreview.com/gene-therapy-research
The National Gene Vector Laboratories (NGVL) was established as a cooperative national effort to produce and distribute vectors for human gene transfer studies.
Proper citation: National Gene Vector Laboratories (RRID:SCR_015944) Copy
Open source software package for comparative sequence analysis using stochastic evolutionary models. Used for analysis of genetic sequence data in particular the inference of natural selection using techniques in phylogenetics, molecular evolution, and machine learning.
Proper citation: HyPhy (RRID:SCR_016162) Copy
Open source web-based system and database that provides access to historical records and trends in the Gene Ontology (GO) and GO annotations (GOA). Used for monitoring changes in the Gene Ontology and their impact on genomic data analysis.
Proper citation: GOTrack (RRID:SCR_016399) 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
A database which houses human subjects clinical trial data. NDCT currently contains data on 13,409 subjects and has access to data on 100,500 subjects from the NIMH Data Archive. Users can also sign up for news updates and watch video tutorials.
Proper citation: National Database for Clinical Trials related to Mental Illness (RRID:SCR_013795) Copy
http://www.ncbi.nlm.nih.gov/pmc/about/pubreader/
A web application which serves as an alternate way to read scientific literature in PubMed Central and Bookshelf. PubReader features an easy-to-read multi-column display, a figure strip for access to figures, and a search function. It is designed especially to support reading on tablets and other smaller devices but is available for reading on laptops and desktops.
Proper citation: PubReader (RRID:SCR_013814) Copy
A simulation software package which hosts a collection of algorithms used to run bioelectric field simulations inside of SCIRun. The software provided in the package may be used for geometric modeling, simulation, and visualization for solving bioelectric field problems.
Proper citation: BioPSE (RRID:SCR_014044) 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
https://wiki.nci.nih.gov/display/LexEVS/LexGrid
LexGrid (Lexical Grid) provides support for a distributed network of lexical resources such as terminologies and ontologies via standards-based tools, storage formats, and access/update mechanisms. The Lexical Grid Vision is for a distributed network of terminological resources. It is the foundation of the National Center for Biomedical Ontology BioPortal interface and web-services, and can parse OBO format, as well as other formats such as OWL. Currently, there are many terminologies and ontologies in existence. Just about every terminology has its own format, its own set of tools, and its own update mechanisms. The only thing that most of these pieces have in common with each other is their incompatibility. This makes it very hard to use these resources to their full potential. We have designed the Lexical Grid as a way to bridge terminologies and ontologies with a common set of tools, formats and update mechanisms. The Lexical Grid is: * accessible through a set of common APIs * joined through shared indices * online accessible * downloadable * loosely coupled * locally extendable * globally revised * available in web-space on web-time * cross-linked The realization of this vision requires three interlocking components, which are: * Standards - access methods and formats need to be published and openly available * Tools - standards based tools must be readily available * Content - commonly used terminologies have to be available for access and download Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: LexGrid (RRID:SCR_006627) Copy
Society leading the fight against kidney disease by educating health professionals, sharing new knowledge, advancing research, and advocating the highest quality care for patients. To accomplish its mission, ASN will: # Educate health professionals by increasing the value of ASN education. # Share new knowledge by improving the quality and expanding the reach of ASN''s communications, including maintaining the premier publications in kidney disease. # Promote the highest quality care by serving as the professional organization informing health policy in kidney disease. # Advance patient care and research in kidney disease by strengthening the pipeline of clinicians, researchers, and educators. To accomplish this goal, ASN will: ## Implement a strategy to increase interest in nephrology careers, which includes promoting diversity within the nephrology workforce. ## Help fund travel to ASN educational activities for physicians and researchers training in the field of kidney disease. ## Use the ASN Grants Program to support outstanding research and foster career development. # Continue to bolster the ASN infrastructure, which includes: ## Increasing diversityincluding age and experience, ethnicity, and genderat all levels of the society. ## Providing avenues for helping ASN members facilitate professional exchange. ## Expanding ASN membership. ## Increasing the ASN Council-Designated Endowment Fund (independent of operational budget) to support grants and other priorities
Proper citation: ASN - American Society of Nephrology (RRID:SCR_006709) Copy
http://www.ncbcs.org/biositemaps/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. A controlled terminology of resources, which is used to improve the sensitivity and specificity of web searches. It includes ''resource_type'', ''area of research'', and ''activity''. It is under development by a number of NIH-funded researchers who have a combined interest in classification of biomedical resources. The biositemaps site is no longer available but the biomedical resource ontology is still available via bioportal Biomedical Resource Ontology (BRO).
Proper citation: Biomedical Resource Ontology (RRID:SCR_004443) Copy
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Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
