Tools   Select Another Resource Report Type

http://www.compucell3d.org/

Open-source simulation environment for multi-cell, single-cell-based modeling of tissues, organs and organisms. It uses Cellular Potts Model to model cell behavior.

Proper citation: CompuCell3D (RRID:SCR_003052) Copy   

•   Source: SciCrunch Registry

http://www.cpc.unc.edu/projects/addhealth

Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.

Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy   

•   Source: SciCrunch Registry

http://www.orbitproject.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on May 29, 2014. The orbit project was a registry of biomedical resources.

Proper citation: OrbitProject (RRID:SCR_010463) Copy   

•   Source: SciCrunch Registry

http://ods.od.nih.gov/Research/CARDS_Database.aspx

Database of federally funded research projects pertaining to dietary supplements. CARDS contains projects funded by the United States Department of Agriculture (USDA), the Department of Defense (DOD) and the Institutes and Centers (ICs) of the National Institutes of Health (NIH) beginning with fiscal year 1999, the first year that NIH ICs began reporting research related to dietary supplements. Projects funded by other Federal agencies will be added to CARDS as they become available. The Office of Dietary Supplements (ODS) will post notices on its website and listserv when CARDS updates are completed. Codes assigned to each research project allow the CARDS user to identify: * research related to specific dietary supplement ingredients; for example, vitamin E or St. John''''s wort * the type of study; for example, a Phase III study or an animal study * health outcomes or biological effects; for example, osteoporosis or antioxidant function * whether the research is directly related or indirectly related to dietary supplements. For example, a clinical trial comparing bone density in women given a daily calcium supplement versus a placebo would be classified as directly related to dietary supplements. A study examining the activation of steroid hormone receptors by supplemental vitamin D in cell culture would be classified as indirectly related to dietary supplements because the direct physiological or health effects of vitamin D supplementation are not being studied. A search of the CARDS database can be used to sort and tabulate information for a variety of purposes. For example, a researcher may want to know which ICs at the NIH fund research on herbal supplement ingredients. A consumer may want to know if the Federal government is supporting research on a popular dietary supplement ingredient such as vitamin C.

Proper citation: CARDS Database (RRID:SCR_009011) Copy   

•   Source: SciCrunch Registry

http://www.jcvi.org/mpidb

Database that collects and provides all known physical microbial interactions. Currently, 24,295 experimentally determined interactions among proteins of 250 bacterial species/strains can be browsed and downloaded. These microbial interactions have been manually curated from the literature or imported from other databases (IntAct, DIP, BIND, MINT) and are linked to 26,578 experimental evidences (PubMed ID, PSI-MI methods). In contrast to these databases, interactions in MPIDB are further supported by 68,346 additional evidences based on interaction conservation, co-purification, and 3D domain contacts (iPfam, 3did). (spoke/matrix) binary interactions inferred from pull-down experiments are not included.

Proper citation: MPIDB (RRID:SCR_001898) Copy   

•   Source: SciCrunch Registry

http://ecogene.org/

Database that contains updated information about the Escherichia coli K-12 genome and proteome sequences, including extensive gene bibliographies. Users are able to download customized tables, perform Boolean query comparisons, generate sets of paired DNA sequences, and download any E. coli K-12 genomic DNA sub-sequence. BLAST functions, microarray data, an alphabetical index of genes, and gene overlap queries are also available. The Database Table Downloads Page provides a full list of EG numbers cross-referenced to the new cross-database ECK numbers and other common accession numbers, as well as gene names and synonyms. Monthly release archival downloads are available, but the live, daily updated version of EcoGene is the default mysql database for download queries.

Proper citation: EcoGene (RRID:SCR_002437) Copy   

•   Source: SciCrunch Registry

http://dejavu.vbi.vt.edu/dejavu/

Deja vu is a database of extremely similar Medline citations. Many, but not all, of which contain instances of duplicate publication and potential plagiarism. Deja vu is a dynamic resource for the community, with manual curation ongoing continuously, and we welcome input and comments. In the scientific research community plagiarism and multiple publications of the same data are considered unacceptable practices and can result in tremendous misunderstanding and waste of time and energy. Our peers and the public have high expectations for the performance and behavior of scientists during the execution and reporting of research. With little chance for discovery and decreasing budgets, yet sustained pressure to publish, or without a clear understanding of acceptable publication practices, the unethical practices of duplicate publication and plagiarism can be enticing to some. Until now, discovery has been through serendipity alone, so these practices have largely gone unchecked.

Proper citation: Deja Vu: a Database of Highly Similar and Duplicate Citations (RRID:SCR_002292) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/proteinclusters

Database of related protein sequences (clusters) consisting of proteins derived from the annotations of whole genomes, organelles and plasmids. It currently limited to Archaea, Bacteria, Plants, Fungi, Protozoans, and Viruses. It contains annotation information, publications, domains, structures, and external links and analysis tools including multiple alignments, phylogenetic trees, and genomic neighborhoods (ProtMap). Data is available for download via Protein Clusters FTP

Proper citation: Protein Clusters (RRID:SCR_003459) Copy   

•   Source: SciCrunch Registry

http://senselab.med.yale.edu/brainpharm/

A database to support research on drugs for the treatment of different neurological disorders. It contains agents that act on neuronal receptors and signal transduction pathways in the normal brain and in nervous disorders. It enables searches for drug actions at the level of key molecular constituents, cell compartments and individual cells, with links to models of these actions.

Proper citation: Brain Pharmacological Database (RRID:SCR_003042) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/gene/about-generif

A database and annotation tool that provides a simple mechanism to allow scientists to add to the functional annotation of genes described in Gene. To be processed, a valid Gene ID must exist for the specific gene, or the Gene staff must have assigned an overall Gene ID to the species. The latter case is implemented via records in Gene with the symbol NEWENTRY.

Proper citation: Gene Reference into Function (RRID:SCR_003436) Copy   

•   Source: SciCrunch Registry

https://dpcpsi.nih.gov/onr/nrcc

Coordinates nutritional sciences-related research and research training across the National Institutes of Health (NIH) and among Federal Agencies by providing mechanisms to communicate research, research training, policy, and education initiatives. The DNRC facilitates the exchange of information, coordinates workshops and seminars on critical issues, encourages national and international research collaborations, and serves as the NIH primary point of contact for the Department of Health and Human Services (DHHS) and other agencies, departments, and organizations in matters pertaining to nutritional sciences and physical activity. Through its dedicated efforts to promote scientific policy reviews, innovative research, interagency collaboration, and technical advancements, the DNRC strives to define the increasing roles of nutritional sciences and physical activity in health promotion and disease prevention and treatment.

Proper citation: NIH Division of Nutrition Research Coordination (RRID:SCR_001469) Copy   

•   Source: SciCrunch Registry

http://www.webarraydb.org/webarray/index.html

An open source integrated microarray database and analysis suite that features convenient uploading of data for storage in a MIAME (Minimal Information about a Microarray Experiment) compliant fashion. It allows data to be mined with a large variety of R-based tools, including data analysis across multiple platforms. Different methods for probe alignment, normalization and statistical analysis are included to account for systematic bias. Student's t-test, moderated t-tests, non-parametric tests and analysis of variance or covariance (ANOVA/ANCOVA) are among the choices of algorithms for differential analysis of data. Users also have the flexibility to define new factors and create new analysis models to fit complex experimental designs. All data can be queried or browsed through a web browser. The computations can be performed in parallel on symmetric multiprocessing (SMP) systems or Linux clusters.

Proper citation: WebArrayDB (RRID:SCR_005577) Copy   

•   Source: SciCrunch Registry

http://www.chori.org/

CHORI is the internationally renowned biomedical research institute of Children''s Hospital and Research Center at Oakland. With world-class scientists and research centers known both nationally and internationally in multiple fields, CHORI is 5th in the nation for National Institutes of Health pediatric research funding. Bridging basic science and clinical research in the treatment and prevention of human disease, CHORI is a leader in translational research, providing cures for blood diseases, developing new vaccines for infectious diseases, and discovering new treatment protocols for previously fatal or debilitating conditions. Striving to provide the highest standard of excellence and innovation, CHORI brings together a multidisciplinary collaborative of distinguished investigators in six different Centers of Research: The Center for Cancer Research, The Center for Genetics, The Center for Immunobiology & Vaccine Development, The Center for Nutrition & Metabolism, The Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, and The Center for Sickle Cell Disease & Thalassemia. Within these major areas of focus, CHORI pushes the frontiers of science and of excellence beyond their borders. Among the leading biotech enterprises in the Bay Area, CHORI produced 25 patents in the last 5 years alone. In addition to providing world-class research, CHORI is also a teaching institute, offering unique educational opportunities to high school, college, doctoral and post-doctoral students.

Proper citation: Childrens Hospital Oakland Research Institute (RRID:SCR_005582) Copy   

•   Source: SciCrunch Registry

http://cs.nyu.edu/~bingsun/

NYU Bioinformatics group applies algorithmic, statistical, and mathematical techniques to solve problems of interest to biology, biotechnology and biomedicine. The group focuses on bioinformatics, computational biology and systems biology with many active projects in areas ranging from single molecules to entire populations: Analysis of Single-Molecule/Single-Cell Data, SPM-based Transcriptomic Profiling, Whole-Genome Haplotype Sequencing using SMASH (Single Molecule Approaches to Haplotype Sequencing), SUTTA (Scoring and Unfolding Trimmed Tree Assembler) assembly algorithm, Analysis of Spatio-Temporal Data, Model Checking and Model Building for Systems Biology, GOALIE-based Phenomenological Models and their Verification, Causality Analysis, Causal Models and their Verification, Analysis of EHR (Electronic Health Record Data) and Disease Models (e.g., Chronic Fatigue Syndrome, Congestive Heart Failure, Deep Vein Thrombosis, etc.), Models of Cancer, Applications to Pancreatic Cancer, Polymorphisms and Biomarkers, Strategies for Group Testing, Epidemiological and Bio-Warfare Models, Planning with Large Agent Networks against Catastrophes (PLAN C), Population Genomics, and Genome Wide Association Studies (GWAS). The group has received its funding from Air Force, Army, CCPR, DARPA, NIH, NIST, NSF, NYSTAR, etc. and various other governmental and commercial entities. Currently, the group is part of an NSF funded Expedition in Computing project (CMACS: Center for Modeling and Analysis of Complex Systems at CMU) and collaborates widely, both nationally and internationally. The group is highly multi-disciplinary, attracting researchers and students from mathematics, statistics, computer science, and biology who team up with physicians, physicists, and chemists as well as professionals in their own disciplines. This group is led by Prof. Bud Mishra, a professor of computer science and mathematics at NYU''s Courant Institute of Mathematical Sciences.

Proper citation: NYU Bioinformatics Group (RRID:SCR_005697) Copy   

•   Source: SciCrunch Registry

http://www.mouseimaging.ca/

A unique resource and comprehensive imaging facility combining the latest state-of-the-art digital medical imaging technologies for the characterization of mouse functional genomics. The goals of the Mouse Imaging Centre are: * To provide a variety of medical imaging technologies adapted to studying genetically modified mice. These technologies include magnetic resonance (MR) imaging, micro computed tomography (micro-CT), ultrasound biomicroscopy (UBM), and optical projection tomography (OPT). * To screen large numbers of mice for models of human diseases. * To image an individual mouse over time to observe development, disease progression and responses to experimental treatment. * To develop an exciting team of investigators with expertise in imaging techniques, computer science, engineering, imaging processing, developmental biology and mouse pathology. * To work by collaboration with researchers throughout the world. When we look for human diseases in the human population, we make extensive use of medical imaging. Therefore, it makes sense to have available the same imaging capabilities as we investigate mice for models of human disease. The Mouse Imaging Centre (MICe) has developed high field magnetic resonance imaging microscopy, ultrasound biomicroscopy, micro computed tomography, and optical techniques. With these imaging tools, MICe is screening randomly mutagenized mice to look for phenotypes that represent human diseases and is taking established human disease models in mice and using imaging to follow the progression of disease and response to treatment over time. It is clear that imaging has a major contribution to make to phenotyping genetic variants and to characterizing mouse models. MICe is staffed by an exciting new team of about 30 investigators with expertise in imaging techniques, computer science, engineering, imaging processing, developmental biology and mouse pathology. The Mouse Imaging Centre (MICe) is not a fee-for-service facility but works through collaborations. Services include: * Projects involving MicroCT are available as a fee for service. * We will eventually move to the same model above with MRI. * Ultrasound Biomicroscopy is used for cardiac, embryo and cancer studies and is available as fee for service at $100 per study or in some cases on a collaborative basis. * Optical Projection Tomography has only limited availability on a collaborative basis. Mouse Atlas As our images are inherently three-dimensional, we will be able to make quantitative measures of size and volume. With this in mind, we are developing a mouse atlas showing the normal deviation of organ sizes. This atlas is an important resource for biologists as it has the potential to eliminate the need to sacrifice as many controls when making comparisons with mutants. Mouse Atlas Examples: * Variational Mouse Brain Atlas * Cerebral Vascular Atlas of the CBA Mouse * Neuroanatomy Atlas of the C57Bl/6j Mouse * Vascular Atlas of the Developing Mouse Embryo * Micro-CT E15.5 Mouse Embryo Atlas

Proper citation: MICe - Mouse Imaging Centre (RRID:SCR_006145) Copy   

•   Source: SciCrunch Registry

http://www.jobs.nih.gov/

A listing of all current openings across the NIH. You may search for NIH Jobs, browse job descriptions, view all descriptions or use the quick links.

Proper citation: Jobs(at)NIH (RRID:SCR_006471) Copy   

•   Source: SciCrunch Registry

https://www.researchmatch.org/

Free and secure registry to bring together two groups of people who are looking for one another: (1) people who are trying to find research studies, and (2) researchers who are looking for people to participate in their studies. It has been developed by major academic institutions across the country who want to involve you in the mission of helping today''''s studies make a real difference for everyone''''s health in the future. Anyone can join ResearchMatch. Many studies are looking for healthy people of all ages, while some are looking for people with specific health conditions. ResearchMatch can help ''''match'''' you with any type of research study, ranging from surveys to clinical trials, always giving you the choice to decide what studies may interest you.

Proper citation: ResearchMatch (RRID:SCR_006387) Copy   

•   Source: SciCrunch Registry

http://www.humanconnectomeproject.org/

A multi-center project comprising two distinct consortia (Mass. Gen. Hosp. and USC; and Wash. U. and the U. of Minn.) seeking to map white matter fiber pathways in the human brain using leading edge neuroimaging methods, genomics, architectonics, mathematical approaches, informatics, and interactive visualization. The mapping of the complete structural and functional neural connections in vivo within and across individuals provides unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve conclusions about the living human brain. The HCP is being developed to employ advanced neuroimaging methods, and to construct an extensive informatics infrastructure to link these data and connectivity models to detailed phenomic and genomic data, building upon existing multidisciplinary and collaborative efforts currently underway. Working with other HCP partners based at Washington University in St. Louis they will provide rich data, essential imaging protocols, and sophisticated connectivity analysis tools for the neuroscience community. This project is working to achieve the following: 1) develop sophisticated tools to process high-angular diffusion (HARDI) and diffusion spectrum imaging (DSI) from normal individuals to provide the foundation for the detailed mapping of the human connectome; 2) optimize advanced high-field imaging technologies and neurocognitive tests to map the human connectome; 3) collect connectomic, behavioral, and genotype data using optimized methods in a representative sample of normal subjects; 4) design and deploy a robust, web-based informatics infrastructure, 5) develop and disseminate data acquisition and analysis, educational, and training outreach materials.

Proper citation: MGH-USC Human Connectome Project (RRID:SCR_003490) Copy   

•   Source: SciCrunch Registry

http://elementsofmorphology.nih.gov/

Data set of standardized terms used to describe human morphology including definitions of terms for the craniofacies in general, the major components of the face, and the hands and feet. This provides a uniform and internationally accepted terms to describe the human phenotype.

Proper citation: elements of morphology (RRID:SCR_003707) Copy   

•   Source: SciCrunch Registry

http://www.med.uc.edu/cardio_bio/

Our 24 faculty members approach the Research and Training in Cardiovascular Biology program from different subspecialties that include genetics, metabolism, development, cellular biology, systems biology, structural biology, biophysics, pharmacology, molecular biology, bioinformatics and biochemistry. While these subspecialties are clearly diverse, our faculty collaboratively leverages these areas toward the common goal of understanding cardiovascular disease from the gene all the way up to integrated organism function (systems biology). This diverse array of subspecialties provides a truly unique training environment that few centers can match. Another critical aspect of our training program is our steadfast commitment to a superior and nurturing training environment for our predoctoral trainees, postdoctoral trainees and clinician-scientists. Our training faculty are uniformly committed to monitoring our personnel for success in every way possible, to not only ensure their future placement in the academic ranks but to also build a stronger cardiovascular community around the country. The current National Institutes of Health-sponsored Research and Training in Cardiovascular Biology was instituted in 1978 by Arnold Schwartz, MD, PhD. This program has trained more than 120 scientists, who have pursued independent research careers and are holding prominent scientific positions worldwide. Our trainees have been distinguished as chairs of basic science departments, directors of centers or pharmaceutical companies, clinical directors and tenured faculty members in academic research. The overall emphasis continues to focus on integrative training and well-rounded knowledge of the fundamentals in biochemical, molecular, physiological and pharmacological underpinnings of cardiovascular disease. Dr. Schwartz has been a constant guiding force since the program was established. The University of Cincinnati, with Cincinnati Children's, has also developed a reputation as a leading center for the generation and analysis of genetically modified mouse models for interrogation of gene-disease relationships in the heart. This theme has been expanded to incorporate molecular genomics, proteomics and bioinformatics, as we continue to be among the leaders in the nation in molecular pathway analysis associated with single gene manipulations in the hearts of mice. Most faculty and trainees are using these approaches, but they are also well-versed in many other aspects of cardiovascular science, including excellence in basic physiology, pharmacology, biochemistry, structural biology and molecular biology. Thus, we are a rare conglomeration of faculty in which all aspects of cardiovascular biology are practiced, starting with cutting-edge molecular and genetic approaches, spanning more traditional cellular and whole animal approaches to build an integrated network of functional and disease-relevant data and extending to translational research incorporating cell therapy.

Proper citation: University of Cincinnati Research and Training in Cardiovascular Biology (RRID:SCR_003860) Copy   

•   Source: SciCrunch Registry