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http://www.icn.ucl.ac.uk/motorcontrol/imaging/suit.htm
High-resolution atlas template of the human cerebellum and brainstem, based on the anatomy of 20 young healthy individuals. The atlas is spatially unbiased, i.e. the location of each structure is equal to the expected location of that structure across individuals in MNI space. At the same time, the new template preserves the anatomical detail of cerebellar structures through a nonlinear atlas-generation algorithm. By using automated nonlinear normalization methods, a more accurate intersubject-alignment than current whole-brain methods can be achieved. The toolbox allows you to: * Automatically isolate cerebellar structures from the cerebral cortex based on an anatomical image * Achieve accurate anatomical normalization of cerebellar structures * Normalize functional imaging data for fMRI group analysis * Normalize focal cerebellar lesions for lesion-symptom mapping * Use Voxel-based morphometry (VBM) to determine patterns of cerebellar degeneration or growth * Use a probabilisitc atlas in SUIT space to assign locations to different cerebellar lobuli in an unbiased and informed way * Automatically define ROIs for specific cerebellar lobuli and summarize function and anatomical data * Improve normalization of the deep cerebellar nuclei using an ROI-driven normalization. The suit-toolbox requires Matlab (Version 6.5 and higher) and SPM. The newest version only supports SPM8, although it likely runs under SPM2 or 5 as well. A standalone version for the suit-toolbox is not planned. Usage of the isolation or normalization functions, however, does not require that the analysis is conducted under SPM.
Proper citation: Spatially unbiased atlas template of the cerebellum and brainstem (RRID:SCR_004969) Copy
Platform for large-scale, automated synthesis of functional magnetic resonance imaging (fMRI) data extracted from published articles. It''s a website wrapped around a set of open-source Python and JavaScript packages. Neurosynth lets you run crude but useful analyses of fMRI data on a very large scale. You can: * Interactively visualize the results of over 3,000 term-based meta-analyses * Select specific locations in the human brain and view associated terms * Browse through the nearly 10,000 studies in the database Their ultimate goal is to enable dynamic real-time analysis, so that you''ll be able to select foci, tables, or entire studies for analysis and run a full-blown meta-analysis without leaving your browser. You''ll also be able to do things like upload entirely new images and obtain probabilistic estimates of the cognitive states most likely to be associated with the image.
Proper citation: NeuroSynth (RRID:SCR_006798) Copy
Center dedicated to understanding and treatment of neurological diseases by creating and using imaging methods to study human nervous system. Dedicated to research imaging of human brain. Brain structure is imaged using anatomical Magnetic Resonance Imaging (aMRI) while brain physiology is imaged using Positron Emission Tomography (PET), Magnetic Resonance Spectroscopy (MRS), functional MRI (fMRI) and magnetoencephalography (MEG). BIC maintains linkages with clinical, clinical research and basic research communities within Montreal Neurological Institute (MNI), McGill University and has collaborations across Quebec, Canada, USA and internationally.
Proper citation: McConnell Brain Imaging Center (RRID:SCR_008364) Copy
http://www.nihclinicalcollection.com
A plated array of approximately 450 small molecules that have a history of use in human clinical trials. The collection was assembled by the National Institutes of Health (NIH) through the Molecular Libraries Roadmap Initiative as part of its mission to enable the use of compound screens in biomedical research. Similar collections of FDA approved drugs have proven to be rich sources of undiscovered bioactivity and therapeutic potential. The clinically tested compounds in the NCC are highly drug-like with known safety profiles. These compounds can provide excellent starting points for medicinal chemistry optimization and, for high-affinity targets, may even be appropriate for direct human use in new disease areas.
Proper citation: NIH Clinical Collection (RRID:SCR_007349) Copy
DoTS (Database Of Transcribed Sequences) is a human and mouse transcript index created from all publicly available transcript sequences. The input sequences are clustered and assembled to form the DoTS Consensus Transcripts that comprise the index. These transcripts are assigned stable identifiers of the form DT.123456 (and are often referred to as dots). The transcripts are in turn clustered to form putative DoTS Genes. These are assigned stable identifiers of the form DG.1234356. As of September 1, 2004, the DoTS annotation team has manually annotated 43,164 human and 78,054 mouse DoTS Transcripts (DTs), corresponding to 3,939 human and 7,752 mouse DoTS Genes (DGs). Use the manually annotated gene query to see the DoTS Transcripts that have been manually annotated. The focus of the DoTS project is integrating the various types of data (e.g., EST sequences, genomic sequence, expression data, functional annotation) in a structured manner which facilitates sophisticated queries that are otherwise not easy to perform. DoTS is built on the GUS Platform which includes a relational database that uses controlled vocabularies and ontologies to ensure that biologically meaningful queries can be posed in a uniform fashion. An easy way to start using the site is to search for DoTS Transcripts using an existing cDNA or mRNA sequence. Click on the BLAST tab at the top of the page and enter your sequence in the form provided. All the transcripts with significant sequence similarity to your query sequence will be displayed. Or use one of the provided queries to retrieve transcripts using a number of criteria. These queries are listed on the query page, which can also be reached by clicking on the tab marked query at the top of the page. Finally, the boolean query page allows these queries to be combined in a variety of ways. Sponsors: Funding provided by -NIH grant RO1-HG-01539-03 -DOE grant DE-FG02-00ER62893
Proper citation: Database of Transcribed Sequences (RRID:SCR_002334) Copy
http://sonorus.princeton.edu/hefalmp/
HEFalMp (Human Experimental/FunctionAL MaPper) is a tool developed by Curtis Huttenhower in Olga Troyanskaya's lab at Princeton University. It was created to allow interactive exploration of functional maps. Functional mapping analyzes portions of these networks related to user-specified groups of genes and biological processes and displays the results as probabilities (for individual genes), functional association p-values (for groups of genes), or graphically (as an interaction network). HEFalMp contains information from roughly 15,000 microarray conditions, over 15,000 publications on genetic and physical protein interactions, and several types of DNA and protein sequence analyses and allows the exploration of over 200 H. sapiens process-specific functional relationship networks, including a global, process-independent network capturing the most general functional relationships. Looking to download functional maps? Keep an eye on the bottom of each page of results: every functional map of any kind is generated with a Download link at the bottom right. Most functional maps are provided as tab-delimited text to simplify downstream processing; graphical interaction networks are provided as Support Vector Graphics files, which can be viewed using the Adobe Viewer, any recent version of Firefox, or the excellent open source Inkscape tool.
Proper citation: Human Experimental/FunctionAL MaPper: Providing Functional Maps of the Human Genome (RRID:SCR_003506) Copy
IPI provides a top level guide to the main databases (UniProtKB/Swiss-Prot, UniProtKB/TrEMBL, RefSeq, Ensembl, TAIR, H-InvDB, Vega) that describe the proteomes of higher eukaryotic organisms. IPI: :1. effectively maintains a database of cross references between the primary data sources :2. provides minimally redundant yet maximally complete sets of proteins for featured species (one sequence per transcript) :3. maintains stable identifiers (with incremental versioning) to allow the tracking of sequences in IPI between IPI releases. IPI is updated monthly in accordance with the latest data released by the primary data sources. As previously announced, the closure of IPI has been proposed for some time. Replacement data sets are now available through UniProt for human and mouse; sets for the other species contained within IPI are expected to be included as part of the UniProt release 2011_07. To allow users time to transition to using the new UniProt data sets, IPI releases will continue to be produced throughout the summer. The final release will be made in September 2011. Thereafter, the IPI website will cease to be maintained, although previous releases of the dataset will continue to be available from the FTP site. We would like to thank our users for their support and interest in this service.
Proper citation: IPI (RRID:SCR_003012) Copy
http://www.biobanque-picardie.com/index_En.php
A secure repository of biological samples and data dedicated for medical and research purposes. These biological samples are linked to consenting patient relative data. Biobanque de Picardie provides quality and traceability services for establishment, conservation and use of biological samples collections. It houses collections of human tissue in a variety of areas of disease. Samples are used in basic research and translational studies, physiopathology of diseases and identification of new diagnostic, and as prognostic or therapeutic biomarkers. Biobanque de Picardie also develops healthy or pathological human primary stem cell banks, such as: mesenchymal stem cells in umbilical cord (HUC-MSC), primary hepatocytes (HPH), peripheral blood mononuclear cells (PBMC), and fibroblasts. Biological samples are stored at - 80 degrees C in electric freezers, at - 196 degrees C in liquid nitrogen or -130 degrees C in nitrogen vapor.
Proper citation: Biobanque de Picardie (RRID:SCR_004731) Copy
http://cgap.nci.nih.gov/Chromosomes/Mitelman
The web site includes genomic data for humans and mice, including transcript sequence, gene expression patterns, single-nucleotide polymorphisms, clone resources, and cytogenetic information. Descriptions of the methods and reagents used in deriving the CGAP datasets are also provided. An extensive suite of informatics tools facilitates queries and analysis of the CGAP data by the community. One of the newest features of the CGAP web site is an electronic version of the Mitelman Database of Chromosome Aberrations in Cancer. The data in the Mitelman Database is manually culled from the literature and subsequently organized into three distinct sub-databases, as follows: -The sub-database of cases contains the data that relates chromosomal aberrations to specific tumor characteristics in individual patient cases. It can be searched using either the Cases Quick Searcher or the Cases Full Searcher. -The sub-database of molecular biology and clinical associations contains no data from individual patient cases. Instead, the data is pulled from studies with distinct information about: -Molecular biology associations that relate chromosomal aberrations and tumor histologies to genomic sequence data, typically genes rearranged as a consequence of structural chromosome changes. -Clinical associations that relate chromosomal aberrations and/or gene rearrangements and tumor histologies to clinical variables, such as prognosis, tumor grade, and patient characteristics. It can be searched using the Molecular Biology and Clinical (MBC) Associations Searcher -The reference sub-database contains all the references culled from the literature i.e., the sum of the references from the cases and the molecular biology and clinical associations. It can be searched using the Reference Searcher. CGAP has developed six web search tools to help you analyze the information within the Mitelman Database: -The Cases Quick Searcher allows you to query the individual patient cases using the four major fields: aberration, breakpoint, morphology, and topography. -The Cases Full Searcher permits a more detailed search of the same individual patient cases as above, by including more cytogenetic field choices and adding search fields for patient characteristics and references. -The Molecular Biology Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to gene rearrangements as a consequence of cytogenetic aberrations. -The Clinical Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to clinical associations of cytogenetic aberrations and/or gene rearrangements. -The Recurrent Chromosome Aberrations Searcher provides a way to search for structural and numerical abnormalities that are recurrent, i.e., present in two or more cases with the same morphology and topography. -The Reference Searcher queries only the references themselves, i.e., the references from the individual cases and the molecular biology and clinical associations. Sponsors: This database is sponsored by the University of Lund, Sweden and have support from the Swedish Cancer Society and the Swedish Children''s Cancer Foundation
Proper citation: Mitelman Database of Chromosome Aberrations in Cancer (RRID:SCR_012877) Copy
IRIS is a toxicology data file on the National Library of Medicine''s (NLM) Toxicology Data Network. It contains data in support of human health risk assessment. It is compiled by the U.S. Environmental Protection Agency (EPA) and contains over 500 chemical records. It is a compilation of electronic reports on specific substances found in the environment and their potential to cause human health effects. IRIS was initially developed for EPA staff in response to a growing demand for consistent information on substances for use in risk assessments, decision-making and regulatory activities. The information in IRIS is intended for those without extensive training in toxicology, but with some knowledge of health sciences. The Integrated Risk Information System (IRIS) is an electronic database containing information on human health effects that may result from exposure to various substances in the environment. IRIS is prepared and maintained by the EPAs National Center for Environmental Assessment (NCEA) within the Office of Research and Development (ORD). The heart of the IRIS system is its collection of searchable documents that describe the health effects of individual substances and that contain descriptive and quantitative information in the following categories: -Noncancer effects: Oral reference doses and inhalation reference concentrations (RfDs and RfCs, respectively) for effects known or assumed to be produced through a nonlinear (possibly threshold) mode of action. In most instances, RfDs and RfCs are developed for the noncarcinogenic effects of substances. -Cancer effects: Descriptors that characterize the weight of evidence for human carcinogenicity, oral slope factors, and oral and inhalation unit risks for carcinogenic effects. Where a nonlinear mode of action is established, RfD and RfC values may be used.
Proper citation: Integrated Risk Information System (RRID:SCR_013005) Copy
THIS RESOURCE IS NO LONGER IN SERVICE.Documented on April 14,2022. Database of comprehensive information on the approximately 600 prokaryote species that are present in the human oral cavity. The majority of these species are uncultivated and unnamed, recognized primarily by their 16S rRNA sequences. The HOMD presents a provisional naming scheme for the currently unnamed species so that strain, clone, and probe data from any laboratory can be directly linked to a stably named reference entity. The HOMD links sequence data with phenotypic, phylogenetic, clinical, and bibliographic information. Full and partial oral bacterial genome sequences determined as part of this project and the Human Microbiome Project, are being added to the HOMD as they become available. HOMD offers easy to use tools for viewing all publicly available oral bacterial genomes. Data is also downloadable.
Proper citation: HOMD (RRID:SCR_012770) Copy
Open-access database of antibodies against human proteins developed through collaboration between Antibodypedia AB and the Nature Publishing Group. It aims to provide the scientific community and antibody distributors alike with information on the effectiveness of specific antibodies in specific applications--to help scientists select the right antibody for the right application. Antibodypedia's mission is to promote the functional understanding of the human proteome and expedite analysis of potential biomarkers discovered through clinical efforts. To this end, they have developed an open-access, curated, searchable database containing annotated and scored affinity reagents to aid users in selecting antibodies tailored to specific biological and biomedical assays. They envisage Antibodypedia as a virtual repository of validated antibodies against all human, and ultimately most model-organism, proteins. Such a tool will be exploitable to identify affinity reagents to document protein expression patterns in normal and pathological states and to purify proteins alone and in complex for structural and functional analyses. They hope to promote characterization of the roles and interplay of proteins and complexes in human health and disease. They encourage commercial providers to submit information regarding their inventory of antibodies with links to quality control data. Independent users can submit their own application-specific experimental data using standard validation criteria (supportive or non-supportive) developed with the assistance of an international advisory board recruited from academic research institutions. Users can also comment on specific antibodies without submitting validation data.
Proper citation: Antibodypedia (RRID:SCR_012782) Copy
http://geneticassociationdb.nih.gov/
The Genetic Association Database is an archive of human genetic association studies of complex diseases and disorders. The goal of this database is to allow the user to rapidly identify medically relevant polymorphism from the large volume of polymorphism and mutational data, in the context of standardized nomenclature. The data is from published scientific papers. Study data is recorded in the context of official human gene nomenclature with additional molecular reference numbers and links. It is gene centered. That is, each record is a record of a gene or marker. If a study investigated 6 genes for a particular disorder, there will be 6 records. Anyone may view this database and anyone may submit records. You do not have to be an author on the original study to submit a record. All submitted records will be reviewed before inclusion in the archive. Both genetic and environmental factors contribute to human diseases. Most common diseases are influenced by a large number of genetic and environmental factors, most of which individually have only a modest effect on the disease. Though genetic contributions are relatively well characterized for some monogenetic diseases, there has been no effort at curating the extensive list of environmental etiological factors. From a comprehensive search of the MeSH annotation of MEDLINE articles, they identified 3,342 environmental etiological factors associated with 3,159 diseases. They also identified 1,100 genes associated with 1,034 complex diseases from the NIH Genetic Association Database (GAD), a database of genetic association studies. 863 diseases have both genetic and environmental etiological factors available. Integrating genetic and environmental factors results in the etiome, which they define as the comprehensive compendium of disease etiology.
Proper citation: Genetic Association Database (RRID:SCR_013264) Copy
SYFPEITHI is a database comprising more than 7000 peptide sequences known to bind class I and class II MHC molecules. The entries are compiled from published reports only. It contains a collection of MHC class I and class II ligands and peptide motifs of humans and other species, such as apes, cattle, chicken, and mouse, for example, and is continuously updated. Searches for MHC alleles, MHC motifs, natural ligands, T-cell epitopes, source proteins/organisms and references are possible. Hyperlinks to the EMBL and PubMed databases are included. In addition, ligand predictions are available for a number of MHC allelic products. The database is based on previous publications on T-cell epitopes and MHC ligands. It contains information on: -Peptide sequences -anchor positions -MHC specificity -source proteins, source organisms -publication references Since the number of motifs continuously increases, it was necessary to set up a database which facilitates the search for peptides and allows the prediction of T-cell epitopes. The prediction is based on published motifs (pool sequencing, natural ligands) and takes into consideration the amino acids in the anchor and auxiliary anchor positions, as well as other frequent amino acids. The score is calculated according to the following rules: The amino acids of a certain peptide are given a specific value depending on whether they are anchor, auxiliary anchor or preferred residue. Ideal anchors will be given 10 points, unusual anchors 6-8 points, auxiliary anchors 4-6 and preferred residues 1-4 points. Amino acids that are regarded as having a negative effect on the binding ability are given values between -1 and -3. Sponsors: SYFPEITHI is supported by DFG-Sonderforschungsbereich 685 and theEuropean Union: EU BIOMED CT95-1627, BIOTECH CT95-0263, and EU QLQ-CT-1999-00713.
Proper citation: SYFPEITHI: A Database for MHC Ligands and Peptide Motifs (RRID:SCR_013182) Copy
http://www.strokecenter.org/radiology/
The Internet Stroke Center at Washington University is pleased to offer this module for viewing CT, MR, and angiogram images of cerebrovascular and neurological diseases. While this project is still being perfected -- and many more cases have yet to be added -- we hope that you will find this collection useful in your education and practice. The images presented here are for educational use only. This information may not be used for diagnosis or treatment. All images are protected property of the Internet Stroke Center at Washington University and may not be reproduced without permission. Permission may be granted to students and professionals to borrow images from this site for educational purposes and/or presentations; we just ask that an email be sent detailing both the desired material and the intended use. Please direct all comments, questions, and requests to the Site Editor of the Internet Stroke Center.
Proper citation: Neurology Image Library from The Internet Stroke Center (RRID:SCR_013633) Copy
http://web.stanford.edu/group/barres_lab/brain_rnaseq.html
Database containing RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of cerebral cortex. Collection of RNA-Seq transcriptome and splicing data from glia, neurons, and vascular cells of mouse cerebral cortex. RNA-Seq of cell types isolated from mouse and human brain.
Proper citation: Brain RNA-Seq (RRID:SCR_013736) Copy
Program is performing deep phenotyping of human endocrine pancreas and its interaction with immune system to better understand cellular and molecular events that precede and lead to beta cell loss in Type-1 Diabetes (T1D) and islet dysfunction in Type-2 Diabetes (T2D).
Proper citation: HIRN Human Pancreas Analysis Program (RRID:SCR_016202) Copy
Ratings or validation data are available for this resource
A collaborative research project that supports nPOD approved diabetes investigators by freely providing rare and difficult-to-obtain tissues from type 1 and type 2 diabetes donors. Interested researchers are encouraged to apply to obtain nPOD tissues, or to request access to analyze cases in the nPOD Online Pathology site. Interested donors can contact nPOD directly for more information.
Proper citation: Network for Pancreatic Organ Donors with Diabetes (RRID:SCR_014641) Copy
http://www.informatics.jax.org/humanDisease.shtml
Collection of published and potential mouse models of human disease, discovery of candidate genes and investigation of phenotypic similarity between mouse models and human patients. Mouse mutation, and phenotype and disease model data from Mouse Genome Informatics database are integrated with human gene to disease relationships from the National Center for Biotechnology Information and Online Mendelian Inheritance in Man and human disease to phenotype relationships from the Human Phenotype Ontology.
Proper citation: Human Mouse Disease Connection (RRID:SCR_017522) Copy
http://epifactors.autosome.ru/
Manually curated collection of human epigenetic factors, their complexes, corresponding genes and products.
Proper citation: EpiFactors (RRID:SCR_016956) Copy
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