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It facilitates the search for and dissemination of mass spectra from biologically active metabolites quantified using Gas chromatography (GC) coupled to mass spectrometry (MS). Use the Search Page to search for a compound of your interest, using the name, mass, formula, InChI etc. as query input. Additionally, a Library Search service enables the search of user submitted mass spectra within the GMD. In parallel to the library search, a prediction of chemical sub-groups is performed. This approach has reached beta level and a publication is currently under review. Using several sub-group specific Decision Trees (DTs), mass spectra are classified with respect to the presence of the chemical moieties within the linked (unknown) compound. Prediction of functional groups (ms analysis) facilitates the search of metabolites within the GMD by means of user submitted GC-MS spectra consisting of retention index (n-alkanes, if vailable) and mass intensities ratios. In addition, a functional group prediction will help to characterize those metabolites without available reference mass spectra included in the GMD so far. Instead, the unknown metabolite is characterized by predicted presence or absence of functional groups. For power users this functionality presented here is exposed as soap based web services. Functional group prediction of compounds by means of GC-EI-MS spectra using Microsoft analysis service decision trees All currently available trained decision trees and sub-structure predictions provided by the GMD interface. Table describes the functional group, optional use of an RI system, record date of the trained decision tree, number of MSTs with proportion of MSTs linked to metabolites with the functional group present for each tree. Average and standard deviation of the 50-fold CV error, namely the ratio false over correctly sorted MSTs in the trained DT, are listed. The GMD website offers a range of mass spectral reference libraries to academic users which can be downloaded free of charge in various electronic formats. The libraries are constituted by base peak normalized consensus spectra of single analytes and contain masses in the range 70 to 600 amu, while the ubiquitous mass fragments typically generated from compounds carrying a trimethylsilyl-moiety, namely the fragments at m/z 73, 74, 75, 147, 148, and 149, were excluded.
Proper citation: GMD (RRID:SCR_006625) Copy
http://espript.ibcp.fr/ESPript/ESPript/
A utility, whose output is a PostScript file of aligned sequences with graphical enhancements. Its main input is an ascii file of pre-aligned sequences. Optional files allow further rendering. The program calculates a similarity score for each residue of the aligned sequences. The output shows: * Secondary Structures * Aligned sequences * Similarities * Accessibility * Hydropathy * User-supplied markers * Intermolecular contacts In addition, similarity score can be written in the bfactor column of a pdb file, to enable direct display of highly conserved areas. You can run ESPript from this server with the HTML interface. It is configured for a maximum of 1,000 sequences. Links to webESPript * ENDscript: you can upload a PDB file or enter a PDB code such as 1M85. The programs DSSP and CNS are executed via the interface, so as to obtain an ESPript figure with a lot of structural information (secondary structure elements, intermolecular contacts). You can also find homologous sequences with a BLAST search, perform multiple sequence alignments with MULTALIN or CLUSTALW and create an image with BOBSCRIPT or MOLSCRIPT to show similarities on your 3D structure. * ProDom: you can enter a sequence identifier to find homologous domains, perform multiple sequence alignments with MULTALIN and click on the link to ESPript. * Predict Protein: you can receive a mail in text (do not use the HTML option when you submit your request in Predict Protein) with aligned sequences and numerous information including secondary structure prediction. Click on a special html link to upload your mail in ESPript. * NPS(at): you can execute the programs BLAST and CLUSTALW to obtain multiple alignments. You can predict secondary structure elements and click on the link to ESPript. This program started in the laboratory of Dr Richard Wade at the Institut de Biologie Structurale, Grenoble. It moved later to the Laboratory of Molecular Biophysics in Oxford, then to the Institut de Pharmacologie et de Biologie Structurale in Toulouse. It is now developed in the Laboratoire de BioCristallographie of Dr Richard Haser, Institut de Biologie et de Chimie des Prot��������ines, Lyon and in the Laboratoire de Biologie Mol��������culaire et de Relations Plantes-Organismes, group of Dr Daniel Kahn, Institut National de la Recherche Agronomique de Toulouse.
Proper citation: ESPript 2.2 (RRID:SCR_006587) Copy
The Traumatic Brain Injury Model Systems National Data and Statistical Center (TBINDSC) located at Craig Hospital in Englewood, Colorado, is a central resource for researchers and data collectors within the Traumatic Brain Injury Model Systems (TBIMS) program. The primary purpose of the TBINDSC is to advance medical rehabilitation by increasing the rigor and efficiency of scientific efforts to longitudinally assess the experience of individuals with traumatic brain injury (TBI). The TBINDSC provides technical assistance, training, and methodological consultation to 16 TBIMS centers as they collect and analyze longitudinal data from people with TBI in their communities, and as they conduct research toward evidence-based TBI rehabilitation interventions. The project design includes * The first prospective, longitudinal multi-center study ever conducted which examines the course of recovery and outcomes following the delivery of a coordinated system of acute neurotrauma and inpatient rehabilitation. * Includes large scale follow-up to 20 years post-injury. Available from this site are links to the TBIMS Presentation and TBIMS Update, which has information about the individual model systems and descriptions of the injury and followup data that are being collected. 2007-2012 Project Priorities * Improved long-term outcomes of individuals with TBI by conducting 1-2 site-specific research projects to test innovative approaches that contribute to rehabilitation interventions and evaluating TBI outcomes in accordance with the focus areas identified in NIDRR''s Long-Range Plan. * Improved outcomes for individuals with TBI by participating in at least one collaborative research module project, which may range from pilot research to more extensive studies. * Continued assessment of long-term outcomes of TBI by enrolling at least 35 subjects per year into the longitudinal portion of the TBIMS database. * In carrying out research activities, each Center may select from the following research domains: Health and Function, Employment, Participation and Community Living, and Technology for Access and Function. In addition, each Center must: * Provide a multidisciplinary system of rehabilitation care specifically designed to meet the needs of individuals with TBI. The system must encompass a continuum of care, including emergency medical services, acute care services, acute medical rehabilitation services, and post-acute services; and * Coordinate with the NIDRR funded Model Systems Knowledge Translation Center to provide scientific results and information for dissemination to clinical and consumer audiences.
Proper citation: Traumatic Brain Injury Model Systems National Data and Statistical Center (RRID:SCR_006736) Copy
The Global Proteome Machine Organization was set up so that scientists involved in proteomics using tandem mass spectrometry could use that data to analyze proteomes. The projects supported by the GPMO have been selected to improve the quality of analysis, make the results portable and to provide a common platform for testing and validating proteomics results. The Global Proteome Machine Database was constructed to utilize the information obtained by GPM servers to aid in the difficult process of validating peptide MS/MS spectra as well as protein coverage patterns. This database has been integrated into GPM server pages, allowing users to quickly compare their experimental results with the best results that have been previously observed by other scientists.
Proper citation: Global Proteome Machine Database (GPM DB) (RRID:SCR_006617) Copy
The first publicly-funded text mining center in the world that provides text mining services in response to the requirements of the UK academic community. You can find pointers to sources of information about text mining such as links to: * text mining services provided by NaCTeM * software tools, both those developed by the NaCTeM team and by other text mining groups * seminars, general events, conferences and workshops * tutorials and demonstrations * text mining publications NaCTeM is operated by the University of Manchester with close collaboration with the University of Tokyo.
Proper citation: National Centre for Text Mining (RRID:SCR_006738) Copy
A community-based data facility to support, sustain, and advance the geosciences by providing data services for observational solid earth data from the Ocean, Earth, and Polar Sciences. IEDA systems enable these data to be discovered and reused by a diverse community now and in the future. Data services include data access, data analysis, data compliance, data publication, DOI search, and web services. Desktop apps GeoMapApp and Virtual Ocean are available to explore, visualize and analyze your own data within the context of hundreds of other earth science data from around the world. IEDA is a partnership between EarthChem and the Marine Geoscience Data System (MGDS). EarthChem and MGDS systems include the geochemical databases PetDB and SedDB, the geochemistry data network EarthChem, the Ridge2000 and MARGINS Data Portals, the Academic Seismic Portal field data collection, the Antarctic and Southern Ocean Data System, the Global Multi Resolution Topography synthesis, and the System for Earth Sample Registration SESAR.
Proper citation: Integrated Earth Data Applications (RRID:SCR_006739) Copy
The Anxiety Disorders Association of America (ADAA) is a national nonprofit organization dedicated to the prevention, treatment, and cure of anxiety disorders and to improving the lives of all people who suffer from them. It is the leader in education, training, and research for anxiety and stress-related disorders. ADAA leads the way, improving the lives of millions of people: * Promotes professional and public awareness of anxiety and related disorders and their impact on people''s lives. * Encourages the advancement of scientific knowledge about causes and treatment of anxiety and related disorders. * Links people who need treatment with the health care professionals who provide it. * Helps people find appropriate treatment and develop self-help skills. * Works to reduce the stigma surrounding anxiety and related disorders. ADAA was founded in 1980 as the Phobia Society of America by a diverse group of clinicians and patients. The term anxiety disorder had not yet been coined. Most anxiety disorders were simply called phobias. That changed as researchers discovered links between panic attacks and abnormal blood flow in the brain, learned that anxiety disorders are associated with pervasive social and health consequences, and discovered and tested various therapies and medications to treat anxiety disorders. ADAA adopted its new name in 1990 to reflect the changing and growing field. Over the years ADAA has launched several national educational campaigns to promote awareness about anxiety disorders and encourage people to seek treatment. ADAA has also funded more than $1.5 million in anxiety disorder research. Today ADAA continues to be the voice for those affected by anxiety and anxiety-related disorders. The organization is frequently cited by the media and also provides information and treatment referrals to tens of thousands each year by phone, e-mail, and through this website.
Proper citation: Anxiety Disorders Association of America (RRID:SCR_006578) Copy
Annual report, standard analysis files and an online query system from the national data registry on the end-stage renal disease (ESRD) population in the U.S., including treatments and outcomes. The Annual Data Report is divided into two parts. The Atlas section displays data using graphs and charts. Specific chapters address trends in ESRD patient populations, quality of ESRD care, kidney transplantation outcomes, costs of ESRD care, Healthy People 2010 objectives, chronic kidney disease, pediatric ESRD, and cardiovascular disease special studies. The Reference Tables are devoted entirely to the ESRD population. The RenDER (Renal Data Extraction and Referencing) online data query system allows users to build data tables and maps for the ESRD population. National, state, and county level data are available. USRDS staff collaborates with members of Centers for Medicare & Medicaid Services (CMS), the United Network for Organ Sharing (UNOS), and the ESRD networks, sharing datasets and actively working to improve the accuracy of ESRD patient information.
Proper citation: United States Renal Data System (RRID:SCR_006699) Copy
A set of online services created in support of MIRIAM, a set of guidelines for the annotation and curation of computational models. The core of MIRIAM Resources is a catalogue of data types (namespaces corresponding to controlled vocabularies or databases), their URIs and the corresponding physical URLs or resources. Access to this data is made available via exports (XML) and Web Services (SOAP). MIRIAM Resources are developed and maintained under the BioModels.net initiative, and are free for use by all. MIRIAM Resources are composed of four components: a database, some Web Services, a Java library and this web application. * Database: The core of the system is a MySQL database. It allows us to store the data types (which can be controlled vocabularies or databases), their URIs and the corresponding physical URLs, and other details such as documentation and resource identifier patterns. Each entry contains a diverse set of details about the data type: official name and synonyms, root URI, pattern of identifiers, documentation, etc. Moreover, each data type can be associated with several resources (or physical locations). * Web Services: Programmatic access to the data is available via Web Services (based on Apache Axis and SOAP messages). In addition, REST-based services are currently being developed. This API allows one to not only resolve model annotations, but also to generate appropriate URIs, based upon the provision of a resource name and accession number. A list of available web services, and a WSDL are provided. A browser-based online demonstration of the Web Services is also available to try. * Java Library: A Java library is provided to access the Web Services. The documentation explains where to download it, its dependencies, and how to use it. * Web Application: A Web application, using an Apache Tomcat server, offers access to the whole data set via a Web browser. It is possible to browse by data type names as well as browse by tags. A search engine is also provided.
Proper citation: MIRIAM Resources (RRID:SCR_006697) Copy
http://www.commondataelements.ninds.nih.gov
The purpose of the NINDS Common Data Elements (CDEs) Project is to standardize the collection of investigational data in order to facilitate comparison of results across studies and more effectively aggregate information into significant metadata results. The goal of the National Institute of Neurological Disorders and Stroke (NINDS) CDE Project specifically is to develop data standards for clinical research within the neurological community. Central to this Project is the creation of common definitions and data sets so that information (data) is consistently captured and recorded across studies. To harmonize data collected from clinical studies, the NINDS Office of Clinical Research is spearheading the effort to develop CDEs in neuroscience. This Web site outlines these data standards and provides accompanying tools to help investigators and research teams collect and record standardized clinical data. The Institute still encourages creativity and uniqueness by allowing investigators to independently identify and add their own critical variables. The CDEs have been identified through review of the documentation of numerous studies funded by NINDS, review of the literature and regulatory requirements, and review of other Institute''s common data efforts. Other data standards such as those of the Clinical Data Interchange Standards Consortium (CDISC), the Clinical Data Acquisition Standards Harmonization (CDASH) Initiative, ClinicalTrials.gov, the NINDS Genetics Repository, and the NIH Roadmap efforts have also been followed to ensure that the NINDS CDEs are comprehensive and as compatible as possible with those standards. CDEs now available: * General (CDEs that cross diseases) Updated Feb. 2011! * Congenital Muscular Dystrophy * Epilepsy (Updated Sept 2011) * Friedreich''s Ataxia * Parkinson''s Disease * Spinal Cord Injury * Stroke * Traumatic Brain Injury CDEs in development: * Amyotrophic Lateral Sclerosis (Public review Sept 15 through Nov 15) * Frontotemporal Dementia * Headache * Huntington''s Disease * Multiple Sclerosis * Neuromuscular Diseases ** Adult and pediatric working groups are being finalized and these groups will focus on: Duchenne Muscular Dystrophy, Facioscapulohumeral Muscular Dystrophy, Myasthenia Gravis, Myotonic Dystrophy, and Spinal Muscular Atrophy The following tools are available through this portal: * CDE Catalog - includes the universe of all CDEs. Users are able to search the full universe to isolate a subset of the CDEs (e.g., all stroke-specific CDEs, all pediatric epilepsy CDEs, etc.) and download details about those CDEs. * CRF Library - (a.k.a., Library of Case Report Form Modules and Guidelines) contains all the CRF Modules that have been created through the NINDS CDE Project as well as various guideline documents. Users are able to search the library to find CRF Modules and Guidelines of interest. * Form Builder - enables users to start the process of assembling a CRF or form by allowing them to choose the CDEs they would like to include on the form. This tool is intended to assist data managers and database developers to create data dictionaries for their study forms.
Proper citation: NINDS Common Data Elements (RRID:SCR_006577) Copy
http://commonfund.nih.gov/Proteincapture/
Program that is developing new resources and tools to understand the critical role the multitude of cellular proteins play in normal development and health as well as in disease. These resources will support a wide-range of research and clinical applications that will enable the isolation and tracking of proteins of interest and permit their use as diagnostic biomarkers of disease onset and progression. The program is being implemented in phases, with three Funding Opportunity Announcements (FOAs): * FOA 1: Antigen Production (RFA-RM-10-007) To produce human transcription factor antigens for making monoclonal antibodies or other affinity capture reagents; this effort is already underway. * FOA 2: Anti-Transcription Factor Antibodies Production (RFA-RM-10-017) To optimize and scale anti-transcription factor capture reagent production to develop a community antibody resource. * FOA 3: New Reagent Technology Development and Piloting (RFA-RM-10-018) To develop improvements in the reagent production pipeline with regard to quality, utility, cost, and production scalability. To understand what makes a cell function normally and what may go awry in disease, we need better tools and resources, such as renewable protein capture reagents and probes, to study how proteins work in isolation and how they interact with other proteins, carbohydrates, or DNA regions within a cell. Ideally, this resource would allow us to identify and isolate all proteins within cells, in their various forms the so called proteome to ensure broad application in research and clinical studies aimed at understanding, preventing, detecting and treating disease. Existing protein capture reagents, such monoclonal antibodies, have been developed for a number of protein targets, although these represent only a subset of all proteins comprising the human proteome. In addition, many monoclonal antibodies lack the desired level of specificity and do not reliably target only the protein of interest. This is particularly problematic given the multiple forms of any one protein and the broad range of protein types in the body. The Protein Capture Reagents Program is organized as a pilot program using transcription factors as a test case to examine the feasibility and value of generating a community resource of low cost, renewable affinity reagents for all human proteins. The reagents must be specifically designed for high quality and broad experimental utility in order to meet the growing demands of biomedical researchers. Based on what is learned from these funding initiatives, the program may expand to a larger production effort to provide a broad community resource of human protein capture reagents.
Proper citation: Common Fund Protein Capture Reagents (RRID:SCR_006570) Copy
http://bactibase.pfba-lab-tun.org/main.php
Data repository of bacteriocin natural antimicrobial peptides and includes data collected from published literature as well as high-throughput datasets. The database provides a manually curated annotation of bacteriocin sequences. New bacteriocin submissions are welcome. Various tools have been incorporated for bacteriocin analysis, such as homology search, multiple sequence alignments, Hidden Markov Models, molecular modelling and retrieval through our taxonomy Browser. BACTIBASE should be a useful tool in food preservation or food safety applications and could have implications for the development of new drugs for medical use. BACTIBASE contains calculated or predicted physicochemical properties of 218 bacteriocins produced by both Gram-positive (194) and Gram-negative bacteria (19). They also note the presence of three bacteriocins from the Archaea domain. The database now comprises 31 genera (2009).
Proper citation: BACTIBASE (RRID:SCR_006694) Copy
Repository contains antibody/B cell and T cell epitope information and epitope prediction and analysis tools. Immune epitopes are defined as molecular structures recognized by specific antigen receptors of the immune system, namely antibodies, B cell receptors, and T cell receptors. Immune epitopes from infectious diseases, excluding HIV, and immune-mediated diseases and the accompanying biological information are included.
Proper citation: Immune Epitope Database and Analysis Resource (IEDB) (RRID:SCR_006604) Copy
This website is a life-sciences research wiki hosted on Google Sites and managed by Principal Investigator Christopher Hogue at the National University of Singapore''''s Department of Biological Sciences on behalf of the Mechanobiology Institute of Singapore. Mechanobiology is the study of cellular and molecular systems that either respond to or generate forces. One of the major efforts of the Mechanobiology Institute is THE MANUAL OF CELLULAR AND MOLECULAR FUNCTION, a Wiki inspired online text resource. Brief History: Between 1997-2007 the Hogue Laboratory was located at Mount Sinai Hospital in Toronto where we developed BIND and other bioinformatics resources. Dr. Hogue was affiliated with the University of Toronto as a non-tenure track Associate Professor. Facing funding and staffing cutbacks in 2005, the intellectual property amassed by the group was sold by Mount Sinai Hospital & founders to Thomson-Reuters Scientific in March of 2007. In late 2007 Dr. Hogue moved to Singapore where he is now tenure-track faculty in Southeast Asia''''s Premiere Research University - the National Unviversity of Singapore.
Proper citation: Christopher Hogues Research Lab at the National University of Singapore (RRID:SCR_006725) Copy
A science-based organization focused on developing effective solutions to address the disease of addiction and reduce the risks associated with substance use. CASAColumbia works to: * Close the gap between what is known about addiction and what is actually done to prevent and treat it * Incorporate addiction prevention and treatment into routine health care and medical practice * Explore the possibility of finding a cure Founded by Former U.S. Secretary of Health, Education, and Welfare Joseph A. Califano, Jr., CASA remains the only national organization that assembles under one roof all of the professional skills needed to research and develop proven, effective ways to prevent and treat substance abuse and addiction to all substances - alcohol, nicotine as well as illegal, prescription and performance enhancing drugs - in all sectors of society. CASAColumbia is committed to understanding the science of addiction and its implications for health care, public policy and public education.
Proper citation: CASA (RRID:SCR_006607) Copy
http://painconsortium.nih.gov/
The NIH Pain Consortium was established to enhance pain research and promote collaboration among researchers across the many NIH Institutes and Centers that have programs and activities addressing pain. To this end, the following goals have been identified for the Pain Consortium: * To develop a comprehensive and forward-thinking pain research agenda for the NIH - one that builds on what we have learned from our past efforts. * To identify key opportunities in pain research, particularly those that provide for multidisciplinary and trans-NIH participation. * To increase visibility for pain research - both within the NIH intramural and extramural communities, as well as outside the NIH. The latter audiences include our various pain advocacy and patient groups who have expressed their interests through scientific and legislative channels. * To pursue the pain research agenda through Public-Private partnerships, wherever applicable. This underscores a key dynamic that has been reinforced and encouraged through the Roadmap process.
Proper citation: NIH Pain Consortium (RRID:SCR_006767) Copy
Professional networking site dedicated to those working, studying, or simply interested in the science of the brain. Those with personal and professional interests in neuroscience, neurology, psychology, and all related areas -- those studying neural activities in invertebrates up to the human brain, including brain-like systems and networks are welcome. The NeuroNetwork was built to allow students and researchers to find and interact with each other in a professional environment. You may create searchable profiles with your research interests; start a blog; upload poster presentations and videos; post and search job listings; form a virtual group based on your interests, geographical location, etc.; and view, post, and RSVP to upcoming meetings. And don''t just create a profile for yourself -- create one for your organization, institute, society, or even your lab as well.
Proper citation: NeuroNetwork (RRID:SCR_006761) Copy
https://www.fludb.org/brc/home.spg?decorator=influenza
The Influenza Research Database (IRD) serves as a public repository and analysis platform for flu sequence, experiment, surveillance and related data.
Proper citation: Influenza Research Database (IRD) (RRID:SCR_006641) Copy
Software to determine most stable reference (housekeeping) genes from set of tested candidate reference genes in given sample panel. From this, gene expression normalization factor can be calculated for each sample based geometric mean of user-defined number of reference genes.
Proper citation: geNORM (RRID:SCR_006763) Copy
Model organism database for the social amoeba Dictyostelium discoideum that provides the biomedical research community with integrated, high quality data and tools for Dictyostelium discoideum and related species. dictyBase houses the complete genome sequence, ESTs, and the entire body of literature relevant to Dictyostelium. This information is curated to provide accurate gene models and functional annotations, with the goal of fully annotating the genome to provide a ''''reference genome'''' in the Amoebozoa clade. They highlight several new features in the present update: (i) new annotations; (ii) improved interface with web 2.0 functionality; (iii) the initial steps towards a genome portal for the Amoebozoa; (iv) ortholog display; and (v) the complete integration of the Dicty Stock Center with dictyBase. The Dicty Stock Center currently holds over 1500 strains targeting over 930 different genes. There are over 100 different distinct amoebozoan species. In addition, the collection contains nearly 600 plasmids and other materials such as antibodies and cDNA libraries. The strain collection includes: * strain catalog * natural isolates * MNNG chemical mutants * tester strains for parasexual genetics * auxotroph strains * null mutants * GFP-labeled strains for cell biology * plasmid catalog The Dicty Stock Center can accept Dictyostelium strains, plasmids, and other materials relevant for research using Dictyostelium such as antibodies and cDNA or genomic libraries.
Proper citation: Dictyostelium discoideum genome database (RRID:SCR_006643) Copy
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