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http://www.ncbi.nlm.nih.gov/Web/Newsltr/Spring04/cancer.html

Cancer Chromosomes is an integration of three databases, the NCI/NCBI SKY/M-FISH & CGH Database, the NCI Mitelman Database of Chromosome Aberrations in Cancer, and the NCI Recurrent Aberrations in Cancer, which all focus on various aspects of cancer and cancer genes. The goal of the SKY/M-FISH and CGH database is to provide a public platform for investigators to share and compare their molecular cytogenetic data. The database is open to everyone and all users can view an individual investigator''s public data or compare public cases from different investigators. The information in the Mitelman Database of Chromosome Aberrations in Cancer relates chromosomal aberrations to tumor characteristics, based either on individual cases or associations. All the data have been manually culled from the literature. Complete karyotypes, patient characteristics, and references are found in the Mitelman Database of Chromosome Aberrations in Cancer. Users can search all three databases for cytogenetic, clinical, and/or reference information.

Proper citation: Cancer Chromosomes (RRID:SCR_007575) Copy   

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http://research.nhgri.nih.gov/scid/

IL2Rgbase is a database of mutations in the X-linked gene IL2RG, leading to the autoimmune disease XSCID. Data on mutations in any of the eight exons may be retrieved and examined, as well as intervening sequences.

Proper citation: X-linked SCID mutation database (RRID:SCR_007732) Copy   

•   Source: SciCrunch Registry

http://cddb.nhlbi.nih.gov/cddb/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. This database is intended to serve as a learning tool to obtain curated information for the design of microarray targets to scan collecting duct tissues (human, rat, mouse). The database focuses on regulatory and transporter proteins expressed in the collecting duct, but when collecting duct proteins are a member of a larger family of proteins, common additional members of the family are included even if they have not been demonstrated to be expressed in the collecting duct. An Internet-accessible database has been devised for major collecting duct proteins involved in transport and regulation of cellular processes. The individual proteins included in this database are those culled from literature searches and from previously published studies involving cDNA arrays and serial analysis of gene expression (SAGE). Design of microarray targets for the study of kidney collecting duct tissues is facilitated by the database, which includes links to curated base pair and amino acid sequence data, relevant literature, and related databases. Use of the database is illustrated by a search for water channel proteins, aquaporins, and by a subsequent search for vasopressin receptors. Links are shown to the literature and to sequence data for human, rat, and mouse, as well as to relevant web-based resources. Extension of the database is dynamic and is done through a maintenance interface. This permits creation of new categories, updating of existing entries, and addition of new ones. CDDB is a database that organizes lists of genes found in collecting duct tissues from three mammalian species: human, rat, and mouse. Proteins are divided into categories by family relationships and functional classification, and each category is assigned a section in the database. Each section includes links to the literature and to sequence information for genes, proteins, expressed sequence tags, and related information. The user can peruse a section or use a search engine at the bottom of the web page to search the database for a name or abbreviation or for a link to a sequence. Each entry in the database includes links to relevant papers in the kidney and collecting duct literature. It uses links to PubMed to generate MEDLINE searches for retrieval of references. In addition, each entry includes links to curated sequence data available in LocusLink. Individual links are made to sequence and protein data for human, rat, and mouse. Links are then added as curated sequences become available for proteins identified in the renal collecting duct and for proteins identified in kidney and similar in function or homologous to proteins identified in the collecting duct.

Proper citation: Collecting Duct Database (RRID:SCR_000759) Copy   

•   Source: SciCrunch Registry

http://www.imagescience.org/meijering/software/neuronj/

NeuronJ is an ImageJ plugin to facilitate the tracing and quantification of elongated structures in two-dimensional (2D) images (8-bit gray-scale and indexed color), in particular neurites in fluorescence microscopy images. Sponsors: The development of NeuronJ started while the primary developer ( Dr. Erik Meijering, PhD) was with the Biomedical Imaging Group (collaborating with people from the Laboratory of Cellular Neurobiology) of the Swiss Federal Institute of Technology in Lausanne (EPFL), Switzerland, and was finished while Dr. Meijering was with the Biomedical Imaging Group Rotterdam in the Netherlands.

Proper citation: NeuronJ: An ImageJ Plugin for Neurite Tracing and Quantification (RRID:SCR_002074) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/brain/

Project aimed at revolutionizing understanding of human brain, to show how individual cells and complex neural circuits interact, enable rapid progress in development of new technologies and data analysis tools to treat and prevent brain disorders. BRAIN Initiative encourages collaborations between neurobiologists and scientists from disciplines such as statistics, physics, mathematics, engineering, and computer and information sciences. Institutes and centers contributing to NIH BRAIN Initiative support those research efforts.

Proper citation: BRAIN Initiative (RRID:SCR_006770) Copy   

•   Source: SciCrunch Registry

https://www.bci2000.org/

BCI2000 is a general-purpose system for brain-computer interface (BCI) and adaptive neurotechnology research. It can also be used for data acquisition, stimulus presentation, and brain monitoring applications. The mission of the BCI2000 project is to facilitate research and applications in the areas described. Their vision is that BCI2000 will become a widely used software tool for diverse areas of real-time biosignal processing. In order to achieve this vision, BCI2000 system is available for free for non-profit research and educational purposes. BCI2000 supports a variety of data acquisition systems, brain signals, and study/feedback paradigms. During operation, BCI2000 stores data in a common format (BCI2000 native or GDF), along with all relevant event markers and information about system configuration. BCI2000 also includes several tools for data import/conversion (e.g., a routine to load BCI2000 data files directly into Matlab) and export facilities into ASCII. BCI2000 also facilitates interactions with other software. For example, Matlab scripts can be executed in real-time from within BCI2000, or BCI2000 filters can be compiled to execute as stand-alone programs. Furthermore, a simple network-based interface allows for interactions with external programs written in any programming language. For example, a robotic arm application that is external to BCI2000 may be controlled in real time based on brain signals processed by BCI2000, or BCI2000 may use and store along with brain signals behavioral-based inputs such as eye-tracker coordinates. Because it is based on a framework whose services can support any BCI implementation, the use of BCI2000 provides maximum benefit to comprehensive research programs that operate multiple BCI2000 installations to collect data for a variety of studies. The most important benefits of the system in such situations are: - A Proven Solution - Facilitates Operation of Research Programs - Facilitates Deployment in Multiple Sites - Cross-Platform and Cross-Compiler Compatibility - Open Resource Sponsors: BCI2000 development is sponsored by NIH/NIBIB R01 and NIH/NINDS U24 grants. Keywords: General, Purpose, Systems, Brain, Computer, Interface, Research, Application, Brain, Diverse, Educational, Laboratory, Software, Network, Signals, Behavioral, Eye, Tracker,

Proper citation: Brain Computer Interface 2000 Software Package (RRID:SCR_007346) Copy   

•   Source: SciCrunch Registry

https://confluence.crbs.ucsd.edu/display/NIF/StemCellInfo

Data tables providing an overview of information about stem cells that have been derived from mice and humans. The tables summarize published research that characterizes cells that are capable of developing into cells of multiple germ layers (i.e., multipotent or pluripotent) or that can generate the differentiated cell types of another tissue (i.e., plasticity) such as a bone marrow cell becoming a neuronal cell. The tables do not include information about cells considered progenitor or precursor cells or those that can proliferate without the demonstrated ability to generate cell types of other tissues. The tables list the tissue from which the cells were derived, the types of cells that developed, the conditions under which differentiation occurred, the methods by which the cells were characterized, and the primary references for the information.

Proper citation: National Institutes of Health Stem Cell Tables (RRID:SCR_008359) Copy   

•   Source: SciCrunch Registry

http://okcam.cbi.pku.edu.cn/

OKCAM (Ontology-based Knowledgebase for Cell Adhesion Molecules) is an online resource for human genes known or predicted to be related to the processes of cell adhesion. These genes include members of the cadherin, immunoglobulin/FibronectinIII (IgFn), integrin, neurexin, neuroligin, and catenin families. :We have mapped these genes onto a novel cell adhesion molecule ontology (CAMO) that provides a hierarchical description of cell adhesion molecules and their functions. It is intended to provide a means to facilitate better and better understanding of the global and specific properties of CAMs through their genomic features, regulatory modes, expression patterns and disease associations become clearer. :Cadherins, IgCAMs, Integrins, Neurexins, Neuroligins, Catenins :

Proper citation: Ontology-based Knowledgebase for Human Cell Adhesion Molecules (RRID:SCR_013555) Copy   

•   Source: SciCrunch Registry

http://www.ncbcs.org/biositemaps/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. Biositemaps represent a mechanism for computational biologists and bio-informaticians to openly broadcast and retrieve meta-data about biomedical data, tools and services (i.e., biomedical resources) over the Internet. All Institutions with an interest in biomedical research can publish a biositemap.rdf file on their Internet site. The technology, developed by the Biositemaps Working Group of the NIH Roadmap National Centers of Biomedical Computing (NCBC), addresses (i) locating, (ii) querying, (iii) composing or combining, and (iv) mining biomedical resources. Each site which intends to contribute to the inventory instantiates a file on its Internet site biositemap.rdf which conforms to a defined RDF schema and uses concepts from the Biomedical Resource Ontology to describe the resources. Each biositemap.rdf file is simply a list of controlled metadata about resources (software tools, databases, material resources) that your organization uses or believes are important to biomedical research. The key enabling technologies are the Information Model (IM) which is the list of metadata fields about each resource (resource_name, description, contact_person, resource_type,...) and the Biomedical Resource Ontology (BRO) which is a controlled terminology for the resource_typeand which is used to improve the sensitivity and specificity of web searches. Biositemaps blend the features of Sitemaps (enabling efficient web-content exploration) and RSS Feeds (a mechanism for wide and effective news dissemination). As a hybrid between Sitemaps and RSS feeds, the Biositemap infrastructure facilitates a decentralized, portable, extensible and computationally tractable generation and consumption of meta-data about existent, revised and new resources for biomedical computation. Web browsers, crawlers and robots can discover, accumulate, process, integrate and deliver Biositemaps content to (human or machine) users in a variety of graphical, tabular, computational formats. Biositemaps content allows such web browsers to pool resource-associated metadata from disparate and diverse sites and present it to the user in an integrated fashion. The Biositemaps protocol provides clues, information and directives for all Biositemap web harvesters that point to the existence and content of such biomedical resources at different sites.

Proper citation: Biositemaps (RRID:SCR_001976) Copy   

•   Source: SciCrunch Registry

http://www.ncbcs.org/

The NCBCs are a set of networked computation core facilities for biomedical infrastructure funded under the NIH Common Fund, the National Program of Excellence in Biomedical Computing (NPEBC). There are seven funded Centers that cover systems biology, image processing, biophysical modeling, biomedical ontologies, information integration, and tools for gene-phenotype and disease analysis. The centers will create innovative software programs and other tools that enable the biomedical community to integrate, analyze, model, simulate, and share data on human health and disease. Each Center has Cores that are focused on (1) computational science, (2) biomedical computational science and (3) driving biological projects whose intent is to drive the interaction between computational and biomedical computational science. In addition to the Centers, the NIH has a number of active program announcements to develop collaborations with the biomedical research community��this includes announcements from the Biomedical Information Science and Technology Initiative (BISTI) and the Program for Collaborations with National Centers for Biomedical Computing. There are numerous efforts in education and training that emanate from the Centers and there is an annual all hands meeting.

Proper citation: National Centers for Biomedical Computing (RRID:SCR_010635) Copy   

•   Source: SciCrunch Registry

http://www.ors.od.nih.gov/

The Office of Research Services (ORS) provides support to the NIH research mission by planning, directing and delivering scientific and regulatory activities, public safety, security, and services for the NIH community.

Proper citation: NIH Office of Research Services (RRID:SCR_000987) Copy   

•   Source: SciCrunch Registry

http://oppnet.nih.gov/

OppNet is a trans-NIH initiative to expand the agency's funding of basic behavioral and social sciences research (b-BSSR). Basic-BSSR studies mechanisms and processes that influence behavior at the individual, group, community and population level. Research results lead to new approaches for reducing risky behaviors and improving the adoption of healthy practices. The mission of OppNet is to pursue opportunities for strengthening basic behavioral and social science research (b-BSSR) at the NIH while innovating beyond existing investments. * OppNet advances basic behavioral and social science research through activities and initiatives that build a body of knowledge about the nature of behavior and social systems. * OppNet prioritizes activities and initiatives that focus on basic mechanisms of behavior and social processes; that are relevant to the missions and public health challenges of multiple NIH Institutes, Centers and Offices (ICOs); and that build upon existing NIH investments without replicating them. All NIH Institutes and Centers (ICs) share the mission of supporting b-BSSR. OppNet will also develop a plan for focused multi-year programs across ICs to advance priority topics within b-BSSR.

Proper citation: OppNet - Basic Behavioral and Social Science Opportunity Network (RRID:SCR_003522) Copy   

•   Source: SciCrunch Registry

http://www.molecularbrain.org/

MolecularBrain is an attempt to collect, collates, analyze and present the microarray derived gene expression data from various brain regions side by side. Transcription Profile of any gene in Mouse (online) and Human Brain (not yet) can be accessed as a histogram along with links to access various aspects of that gene. The expression levels were calculated from microarray data deposited at GEO (Gene expression omnibus). The molecular brain database could be searched using the built in search tool with the terms Entrez GeneID, gene symbol, synonym or description. Gene information along with their expression values can be also accessed from the alphabetical list of gene symbols on the footer. The protocol and GEO sample information is available.

Proper citation: Molecular Brain: Transcription Profiles of Mouse and Human Brains (RRID:SCR_008689) Copy   

•   Source: SciCrunch Registry

http://www.ott.nih.gov/erma/

Database and tool for finding and licensing unpatented research materials to for-profit entities. eRMa was developed by the NIH Office of Technology Transfer to expedite the process for transferring unpatented research materials to for-profit entities. NIH researchers make unpatented materials available to companies through internal use licenses executed by the OTT to support the continued advancement of scientific research. Examples of materials include mouse models used to develop new cancer therapies and cell lines used to test new therapies for chronic diseases, such as high blood pressure. An NIH internal use license is a contract that governs the transfer of tangible research materials from NIH to a company for commercial research use.

Proper citation: NIH electronic Research Materials catalogue (RRID:SCR_013151) Copy   

•   Source: SciCrunch Registry

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

PubMatrix is a web-based tool that allows simple text based mining of the NCBI literature search service PubMed using any two lists of keywords terms, resulting in a frequency matrix of term co-occurrence. PubMatrix is a simple way to rapidly and systematically compare any list of terms against any other list of terms in PubMed. It reports back the frequency of co-occurrence between all pairwise comparisons between the two lists as a matrix table. Lists of terms can be anything; gene names, diseases, gene functions, authors, etc. The user can then quickly sort or browse the frequency matrix table to do individual searches independently. This allows the user to build up tables of word relationships in PubMed in the context of your experiments or your scientific interests. This is useful for analyzing combinatorial datasets, as found with multiplex experimental systems, such as cDNA microarrays, genomic, proteomic, or other multiplex comparisons. The PubMatrix database is an archive of previous searches on many topics. Sponsors: PubMatrix is supported by the National Institutes of Health.

Proper citation: PubMatrix (RRID:SCR_008236) Copy   

•   Source: SciCrunch Registry

http://stroke.nih.gov/

Campaign to help educate the public about the symptoms of stroke and the importance of getting to the hospital quickly, with a wide range of materials about stroke prevention, treatment, and rehabilitation available through the site. The campaign includes outreach to consumers and health care professionals using mass media, grassroots outreach, partnerships, and community education.

Proper citation: Know Stroke Campaign (RRID:SCR_008073) Copy   

•   Source: SciCrunch Registry

http://mli.nih.gov/mli/

High throughput screening services to identify small molecules that can be optimized as chemical probes to study the functions of genes, cells, and biochemical pathways, along with medicinal chemistry and informatics. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. The NIH Molecular Libraries Initiative NIH is designed to discover small molecules that interact with biologically important proteins and pathways and to provide open access to the bioassay and chemical data generated by its research centers. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. As these HTS Technologies were not previously available to the public sector, many investigators may not be familiar with the components and requirements of high throughput screening. A key challenge is to identify small molecules effective at modulating a given biological process or disease state. The Molecular Libraries Roadmap, through one of its components, the Molecular Libraries Probe Production Centers Network (MLPCN), offers biomedical researchers access to the large-scale screening capacity, along with medicinal chemistry and informatics necessary to identify chemical probes to study the functions of genes, cells, and biochemical pathways. This will lead to new ways to explore the functions of genes and signaling pathways in health and disease. There are two kinds of data that are available to the scientific community through a dedicated database: Chemical Compounds and Bioassay Results (NCBI). Various types of data, including informative records on substances, compound structures, and biologically active properties of small molecules are housed respectively within PubChem''''s three primary databases: PCSubstance, PCCompound, and PCBioAssay. To date, PubChem contains over 11 million substance records, details about approximately 5.5 million unique compound structures with links to bioassay descriptions, relevant literature, references, and assay data points and over 250 bioassays, a good percentage of which were contributed by the pilot phase of the MLP. The deposition will continue during the current MLPCN phase. NIH anticipates that these projects will also facilitate the development of new drugs, by providing early stage chemical compounds that will enable researchers in the public and private sectors to validate new drug targets, which could then move into the drug-development pipeline. This is particularly true for rare diseases, which may not be attractive for development by the private sector. Funding opportunities are available through the site.

Proper citation: Molecular Libraries Program (RRID:SCR_008847) Copy   

•   Source: SciCrunch Registry

http://trans.nih.gov/bmap/index.htm

The Brain Molecular Anatomy Project is a trans-NIH project aimed at understanding gene expression and function in the nervous system. BMAP has two major scientific goals: # Gene discovery: to catalog of all the genes expressed in the nervous system, under both normal and abnormal conditions. # Gene expression analysis: to monitor gene expression patterns in the nervous system as a function of cell type, anatomical location, developmental stage, and physiological state, and thus gain insight into gene function. In pursuit of these goals, BMAP has launched several initiatives to provide resources and funding opportunities for the scientific community. These include several Requests for Applications and Requests for Proposals, descriptions of which can be found in this Web site. BMAP is also in the process of establishing physical and electronic resources for the community, including repositories of cDNA clones for nervous system genes, and databases of gene expression information for the nervous system. Most of the BMAP initiatives so far have focused on the mouse as a model species because of the ease of experimental and genetic manipulation of this organism, and because many models of human disease are available in the mouse. However, research in humans, other mammalian species, non-mammalian vertebrates, and invertebrates is also being funded through BMAP. For the convenience of interested investigators, we have established this Web site as a central information resource, focusing on major NIH-sponsored funding opportunities, initiatives, genomic resources available to the research community, courses and scientific meetings related to BMAP initiatives, and selected reports and publications. When appropriate, we will also post initiatives not directly sponsored by BMAP, but which are deemed relevant to its goals. Posting decisions are made by the Trans-NIH BMAP Committee

Proper citation: BMAP - Brain Molecular Anatomy Project (RRID:SCR_008852) 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.bioconductor.org/packages/release/bioc/html/ACME.html

A set of tools for analysing tiling array ChIP/chip, DNAse hypersensitivity, or other experiments that result in regions of the genome showing enrichment. It does not rely on a specific array technology (although the array should be a tiling array), is very general (can be applied in experiments resulting in regions of enrichment), and is very insensitive to array noise or normalization methods. It is also very fast and can be applied on whole-genome tiling array experiments quite easily with enough memory.

Proper citation: ACME (RRID:SCR_001464) Copy   

•   Source: SciCrunch Registry