Tools   Select Another Resource Report Type

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   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/IPI

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   

•   Source: SciCrunch Registry

http://www.cvm.ncsu.edu/ccmtr/

The mission of the CCMTR is to promote scientific discovery and facilitate its clinical application to achieve the goal of improving the health of animals and humans. The needs of the patients direct the emphasis of basic research, patient samples provide the critical resource to investigate the basis of disease, and patient participation in clinical studies is required to generate the evidence needed to apply new drugs, vaccines and technology to the broader patient population. Initiatives at the Center are designed to develop the multidisciplinary teams necessary to bring an idea from the lab to the patient. The Center is home to service cores that provide advanced technology, collect and store clinical patient samples, and perform clinical trials to validate new medical interventions. North Carolina State University''s College of Veterinary Medicine (CVM) is a dynamic community whose members are dedicated to preparing veterinarians and veterinarian scientists while advancing animal and human health from the cellular level through entire ecosystems.

Proper citation: Center for Comparative Medicine and Translational Research (RRID:SCR_008299) Copy   

•   Source: SciCrunch Registry

http://www.semel.ucla.edu/creativity/

The purpose of this center is to study the molecular, cellular, systems and cognitive mechanisms that result in cognitive enhancements and explain unusual levels of performance in gifted individuals, including extraordinary creativity. Additionally, by understating the mechanisms responsible for enhancements in performance we may be better suited to intervene and reverse disease states that result in cognitive deficits. One of the key topics addressed by the Center is the biological basis of cognitive enhancements, a topic that can be studied in human subjects and animal models. In the past much of the focus in the brain sciences has been on the study of brain mechanisms that degrade cognitive performance (for example, on mutations or other lesions that cause cognitive deficits). The Tennenbaum Center for the Biology of Creativity at UCLA enables an interdisciplinary team of leading scientists to advance knowledge about the biological bases of creativity. Starting with a pilot project program, a series of investigations was launched, spanning disciplines from basic molecular biology to cognitive neuroscience. Because the concept of creativity is multifaceted, initial efforts targeted refinement of the component processes necessary to generate novel, useful cognitive products. The identified core cognitive processes: 1.) Novelty Generation the ability to flexibly and adaptively generate products that are unique; 2.) Working Memory and Declarative Memory the ability to maintain, and then use relevant information to guide goal-directed performance, along with the capacity to store and retrieve this information; and 3.) Response Inhibition the ability to suppress habitual plans and substitute alternate actions in line with changing problem-solving demands. To study the basic mechanisms underlying these complex brain functions we use translational strategies. Starting from foundational studies in basic neuroscience, we forged an interdisciplinary strategy that permits the most advanced techniques for genetic manipulation and basic neurobiological research to be applied in close collaboration with human studies that converge on the same core cognitive processes. Our integrated research program aims to reveal the genetic architecture and fundamental brain mechanisms underlying creative cognition. The work holds enormous promise for both enhancing healthy cognitive performance and designing new treatments for diverse cognitive disorders. Sponsors: The Tennenbaum Center for the Biology of Creativity was inspired by the vision and generosity of Michael Tennenbaum.

Proper citation: Tennenbaum Center for the Biology of Creativity (RRID:SCR_000668) Copy   

•   Source: SciCrunch Registry

http://metscape.ncibi.org

A software program that allows users to visualize and interpret human metabolim and expression profiling data by providing users with a bioinformatics framework. Its features include bulding and analyzing networks of genes and compounds, identifying enriched pathways from expression profiling data, and visualizing changes in metabolite data.

Proper citation: Metscape (RRID:SCR_014687) Copy   

•   Source: SciCrunch Registry

http://crbs.ucsd.edu/

CRBS is a UCSD organized research unit (ORU) that exists to provide human resources, high technology equipment, and administrative services to researchers engaged in fundamental research on cell structure and function relationships in central nervous system processes, cardiovascular networking, and muscular contraction through multiple scales and modalities. CRBS scientists investigate these processes through invention, refinement, and deployment of sophisticated technologies, especially: - High-powered electron microscopes that reveal three-dimensional cell structures - State-of-the-art X-ray crystallography and magnetic resonance analysis that provide detail on protein structures at high-resolution - Laser-scanning and confocal light microscopes that reveal molecules tagged with fluorescent markers as they traffic within cells and pass transfer signals within and between cells - High performance computing and grid-based integration of distributed data CRBS facilitates an interdisciplinary infrastructure in which people from biology, medicine, chemistry, and physics can work with those from computer science and information technologies in collaborative research. Researchers share interests in the study of complex biological systems at many scales, from the structures of enzymes, proteins, and the body's chemical communications network at atomic and molecular levels, to an organism's physiology, strength, and support at cellular and tissue levels. The CRBS infrastructure integrates resources for high-performance computing, visualization, and database technologies, and the grid-integration of large amounts of archival storage data. The California Institute for Telecommunications and Information Technology (Cal-IT2) and the San Diego Supercomputer Center (SDSC) are collaborators in simulating the activity of biological systems, analyzing the results, and organizing the growing storehouse of biological information. CRBS is an entity evolving as research evolves. It forges interactions with biotechnology and biocomputing companies for technology transfer. Interaction, collaboration, and multiscale research produce new perspectives, reveal fruitful research topics, lead to the development of new technologies and drugs, and train a new generation of researchers in biological systems. Sponsors: CRBS is supported by the University of California at San Diego.

Proper citation: Center for Research in Biological Systems (RRID:SCR_002666) Copy   

•   Source: SciCrunch Registry

http://www.bic.mni.mcgill.ca/

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://neurosynth.org

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   

•   Source: SciCrunch Registry

https://www.pbcconsortium.org/

Portal to provide a repository for beta-cell data, to connect researchers from different backgrounds interested in contributing data, models and/or ideas for new insights into beta-cell biology. Used to understand beta-cell biology and diabetes through a cross-disciplinary approach for the assembly of spatiotemporal multi-scale whole cell models of human pancreatic beta-cells.

Proper citation: The Pancreatic Beta-Cell Consortium (RRID:SCR_016328) Copy   

•   Source: SciCrunch Registry

https://www.t2depigenome.org/

Collects and provides data on the human genome and epigenome to facilitate genetic studies of type 2 diabetes and its complications. A component of the AMP T2D consortium, which includes the National Institute for Diabetes and Digestive and Kidney Diseases (NIDDK) and an international collaboration of researchers.

Proper citation: Diabetes Epigenome Atlas (RRID:SCR_016441) Copy   

•   Source: SciCrunch Registry

http://www.dhal.com/viewboxindex.htm

Software for cephalometric analysis. Customizable. Allows rendering, viewing and measuring of 3D data from CT scanners. Used in orthodontic departments for analysis of the dental and skeletal relationships of a human skull.

Proper citation: Viewbox4, Cephalometric software (RRID:SCR_016481) Copy   

•   Source: SciCrunch Registry

http://www.linkrbrain.eu

An online tool for managing and viewing datasets. Data can be viewed in 2D or 3D with activation points as points clouds or projections on the cortex surface. Data can be imported as a NIfTI file or a list of activation peaks and results can be exported as a PDF file.

Proper citation: linkRbrain (RRID:SCR_014562) Copy   

•   Source: SciCrunch Registry

http://coot.embl.de/g2d/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A database of candidate genes for mapped inherited human diseases. Candidate priorities are automatically established by a data mining algorithm that extracts putative genes in the chromosomal region where the disease is mapped, and evaluates their possible relation to the disease based on the phenotype of the disorder. Data analysis uses a scoring system developed for the possible functional relations of human genes to genetically inherited diseases that have been mapped onto chromosomal regions without assignment of a particular gene. Methodology can be divided in two parts: the association of genes to phenotypic features, and the identification of candidate genes on a chromosonal region by homology. This is an analysis of relations between phenotypic features and chemical objects, and from chemical objects to protein function terms, based on the whole MEDLINE and RefSeq databases.

Proper citation: Candidate Genes to Inherited Diseases (RRID:SCR_008190) Copy   

•   Source: SciCrunch Registry

http://neibank.nei.nih.gov

An integrated resource for genomics and bioinformatics in vision research including expressed sequence tag (EST) data and sequence-verified cDNA clones for multiple eye tissues of several species, web-based access to human eye-specific SAGE data through EyeSAGE, and comprehensive, annotated databases of known human eye disease genes and candidate disease gene loci. All expression- and disease-related data are integrated in EyeBrowse, an eye-centric genome browser. NEIBank provides a comprehensive overview of current knowledge of the transcriptional repertoires of eye tissues and their relation to pathology. The data can be interrogated in several ways. Specific gene names can be entered into the search window. Alternatively, regions of the genome can be displayed. For example, entering two STS markers separated by a semicolon (e.g. RH18061;RH80175) allows the display of the entire chromosomal region associated with the mapping of a specific disease locus. ESTs for each tissue can then be displayed to help in the selection of candidate genes. In addition, sequences can be entered into a BLAST search and rapidly aligned on the genome, again showing eye derived ESTs for the same region. To see the same region at the full UCSC site, cut and paste the location from the position window of the genome browser. EyeBrowse includes a custom track display SAGE data for human eye tissues derived from the EyeSAGE project. The track shows the normalized sum of SAGE tag counts from all published eye-related SAGE datasets centered on the position of each identifiable Unigene cluster. This indicates relative activity of each gene locus in eye. Clicking on the vertical count bar for a particular location will bring up a display listing gene details and linking to specific SAGE counts for each eye SAGE library and comparisons with normalized sums for neural and non-neural tissues. To view or alter settings for the EyeSAGE track on EyeBrowse, click on the vertical gray bar at the left of the display. Other custom tracks display known eye disease genes and mapped intervals for candidate loci for retinal disease, cataract, myopia and cornea disease. These link back to further information at NEIBank.

Proper citation: NEIBank (RRID:SCR_007294) Copy   

•   Source: SciCrunch Registry

https://hirnetwork.org

Network helps to organize and support collaborative research related to loss of functional beta cell mass in Type 1 Diabetes (T1D). Project consists of four independent research initiatives: Consortium on Beta Cell Death and Survival (CBDS), Consortium on Human Islet Biomimetics (CHIB), Consortium on Modeling Autoimmune Interactions (CMAI), Consortium on Targeting and Regeneration (CTAR), and Human Pancreas Analysis Program (HPAP).

Proper citation: Human Islet Research Network (HIRN) (RRID:SCR_014393) Copy   

•   Source: SciCrunch Registry

http://www.seattle.eric.research.va.gov/VETR/Home.asp

The Vietnam Era Twin (VET) Registry is a closed cohort composed of approximately 7,000 middle-aged male-male twin pairs both of whom served in the military during the time of the Vietnam conflict (1964-1975). The Registry is a United States Department of Veterans Affairs (VA) resource that was originally constructed from military records; the Registry has been in existence for almost 20 years. It is one of the largest national twin registries in the US and currently has members living in all 50 states. Initially formed to address questions about the long-term health effects of service in Vietnam, the Registry has evolved into a resource for genetic epidemiological studies of mental and physical health conditions. Several waves of mail and telephone surveys have collected a wealth of health-related information on Registry twins, referred to as members. In addition to twins, selected adult offspring of twins and the mothers of those offspring are also VET Registry members. More recent data collection efforts have focused on specific sets of twin pairs and have conducted detailed clinical or laboratory testing. Selected Vietnam Era Registry Research Studies: * Veteran Health Study * VETSA 2: A Longitudinal Study of Cognitive Aging * Alcoholism Course thought Midlife: A Twin Family Study and Offspring of Twins: G, E and GxE Risk for Alcoholism * GE: Offspring of Twins with Substance Use Disorder * Mechanisms Linking Depression to Cardiovascular Risk (Twins Heart Study 2) * Post-traumatic Stress Disorder and Cardiovascular Disease * Biological Markers for Post-traumatic Stress Disorder (T3) * Memory and the Hippocampus in Vietnam-era Twins with PTSD (Time 3)

Proper citation: Vietnam Era Twin Registry (RRID:SCR_008807) Copy   

•   Source: SciCrunch Registry

http://www.grc.nia.nih.gov/

A research program of the NIA which focuses on neuroscience, aging biology, and translational gerontology. The central focus of the program's research is understanding age-related changes in physiology and the ability to adapt to environmental stress, and using that understanding to develop insight about the pathophysiology of age-related diseases. The IRP webpage provides access to other NIH resources such as the Biological Biochemical Image Database, the Bioinformatics Portal, and the Baltimore Longitudinal Study of Aging., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Intramural Research Program (RRID:SCR_012734) Copy   

•   Source: SciCrunch Registry

http://www.cdc.gov/genomics/hugenet/default.htm

Human Genome Epidemiology Network, or HuGENet, is a global collaboration of individuals and organizations committed to the assessment of the impact of human genome variation on population health and how genetic information can be used to improve health and prevent disease. Its goals include: establishing an information exchange that promotes global collaboration in developing peer-reviewed information on the relationship between human genomic variation and health and on the quality of genetic tests for screening and prevention; providing training and technical assistance to researchers and practitioners interested in assessing the role of human genomic variation on population health and how such information can be used in practice; developing an updated and accessible knowledge base on the World Wide Web; and promoting the use of this knowledge base by health care providers, researchers, industry, government, and the public for making decisions involving the use of genetic information for disease prevention and health promotion. HuGENet collaborators come from multiple disciplines such as epidemiology, genetics, clinical medicine, policy, public health, education, and biomedical sciences. Currently, there are 4 HuGENet Coordinating Centers for the implementation of HuGENet activities: CDC''s Office of Public Health Genomics, Atlanta, Georgia; HuGENet UK Coordinating Center, Cambridge, UK; University of Ioannina, Greece; University of Ottawa , Ottawa, Canada. HuGENet includes: HuGE e-Journal Club: The HuGE e-Journal Club is an electronic discussion forum where new human genome epidemiologic (HuGE) findings, published in the scientific literature in the CDC''s Office of Public Health Genomics Weekly Update, will be abstracted, summarized, presented, and discussed via a newly created HuGENet listserv. HuGE Reviews: A HuGE Review identifies human genetic variations at one or more loci, and describes what is known about the frequency of these variants in different populations, identifies diseases that these variants are associated with and summarizes the magnitude of risks and associated risk factors, and evaluates associated genetic tests. Reviews point to gaps in existing epidemiologic and clinical knowledge, thus stimulating further research in these areas. HuGE Fact Sheets: HuGE Fact Sheets summarize information about a particular gene, its variants, and associated diseases. HuGE Case Studies: An on-line presentation designed to sharpen your epidemiological skills and enhance your knowledge on genomic variation and human diseases. Its purpose is to train health professionals in the practical application of human genome epidemiology (HuGE), which translates gene discoveries to disease prevention by integrating population-based data on gene-disease relationships and interventions. Students will acquire conceptual and practical tools for critically evaluating the growing scientific literature in specific disease areas. HUGENet Publications: Articles related to the HuGENet movement written by our HuGENet collaborators. HuGE Navigator: An integrated, searchable knowledge base of genetic associations and human genome epidemiology, including information on population prevalence of genetic variants, gene-disease associations, gene-gene and gene- environment interactions, and evaluation of genetic tests. HuGE Workshops: HuGENet has sponsored meetings and workshops with national and international partners since 2001. Available are detailed summaries, agendas or the ability to download speaker slides. HuGE Book: Human Genome Epidemiology: A Scientific Foundation for Using Genetic Information to Improve Health and Prevent Disease. (The findings and conclusions in this book are those of the author(s) and do not necessarily represent the views of the funding agency.) HuGENet Collaborators: HuGENet is interested in establishing collaborations with individuals and organizations working on population based research involving genetic information. HuGE Funding: Funding opportunities for specific population-based genetic epidemiology research projects are available. Research initiatives whose aims include assessing the prevalence of human genetic variation, the association between genetic variants and human diseases, the measurement of gene-gene or gene-environment interaction, and the evaluation of genetic tests for screening and prevention are compiled to create a posted listing. Additional information and application details can be found by clicking on the respective links.

Proper citation: Human Genome Epidemiology Network (RRID:SCR_013117) Copy   

•   Source: SciCrunch Registry