NIF is a resource for neuroscientists, built by neuroscientists. Involvement of neuroscientists is critical for continuing improvement of the NIF most importantly in the areas of vocabularies and resources.

1. NIF Vocabularies: The NIF consensus vocabulary, the NIF Standard ontology (NIFSTD), is the basis of our “smart” search technology and it attempts to encompass the various subspecialties of the field of neuroscience. The vocabulary continues to be improved by NIF staff, but community involvement is critical to provide expertise in all areas of neuroscience, point out problems, and offer differing points of view. The NeuroLex Wiki provides the community with an easy way to give feedback and contribute to the NIF vocabulary, which will be incorporated by NIF staff into the NIFSTD. For more on vocabulary, see FAQs 15-16 below.

2. NIF Registry: The NIF Registry is a catalog of resources that has been curated by the NIF curation staff and continues to be improved. NIF would like to register all neuroscience-related Web resources such that they can be easily found by neuroscientists. NIF welcomes your feedback on existing resources and encourages you to recommend additional Web resources that relate to neuroscience to be included in the registry.

NIF currently links to the CRISP (Computer Retrieval of Information on Scientific Projects) database which is a database on federally funded biomedical research projects conducted at universities, hospitals, and other research institutions.  This database is queried each time a search is conducted and relevant abstracts can be viewed from the NIH Grants tab.  The NIF continues to seek out and register relevant, non-profit organizations that provide grants to neuroscientists. If you know of any additional resources, please recommend the resource for inclusion in the NIF. In the meantime, you may also find results under the NIF Registry or the NIF Web tabs.  In the NIF Registry, look for search results that are categorized as a Funding Resource under the Resource Type column. To retrieve results in the NIF Web you may need to include the word “grant” in your search terms.

The NIF currently indexes the ExactAntigen database, which contains product information submitted by reagent provider partners, and millions of Web pages selected from all 750 reagent suppliers. This database is queried each time a search is conducted. Relevant results can be retrieved under the Data Federation tab, by clicking on ExactAntigen under the Antibodies category where antibody information including species, price and links to suppliers can be found.  NIF is working to increase the number of antibody resources and we invite you to recommend a resource. Additional search results for antibodies may also be found under the NIF Web and NIF Registry tabs.

Textpresso has been assembled from indexing a select set of neuroscience journals—and from articles retrieved from keyword searches of PubMed for neuroscience-related terms—focusing the search results to neuroscience related content.  That said, Textpresso searches the full text of research papers—not just the abstract— to find matching search terms, whereas PubMed has a more limited search of article content.  This may help to identify information within articles that may not be available to PubMed.  Another benefit of Textpresso is that its interface provides the ability to further refine searches by the use of categories (e.g. brain region) and filters.  We encourage you to compare results in Textpresso and PubMed, especially using longer search strings, and would appreciate your feedback.  Furthermore, we expect that Textpresso’s corpus of literature will continue to grow as we improve our capabilities.

NIF does not provide direct access to the full articles indexed in the NIF literature archive; however, the NIF does provide access to the relevant articles in PubMed and Google Scholar. If the journal article is open access, or you have an institutional or personal subscription, you will be able to retrieve the full text.

For an up-to-date number of resources (make sure the search field is cleared), refer to the number displayed on the NIF Registry tab. At the time of this update, there are approximately 1000 resources that have been reviewed by a human curator, but the number changes weekly as we find and curate new resources.  Currently, commercial sites are not listed, but we anticipate that this will change within a year.

No; the NIF generally lists only non-profit entities in the NIF Registry; however, some commercial sites are available through the NIF Web.  Our policies on including commercial sites are still under development, so this situation may change.

The NIF offers several search options, and it may be that by expanding or refining a search, the resource will be returned. However, the NIF is not fully populated and we know that resources may be missing. You can include your favorite resource by contacting the NIF team or by recommending a resource online.

If you would like to see a resource added to the NIF Registry, please contact the NIF team or recommend a resource online.

If you would like to see a resource added to the NIF Registry, please contact the NIF team or recommend a resource online.

The NIF is working to register as many relevant resources at level 3 as possible. Registration at level 3 via the NIF Data Federation tools enables NIF to issue a highly-tuned concept-based query against the data in the resource and this takes time on the part of the NIF staff and each resource provider.  Registration at level 3 does not require any re-engineering of the original resource; rather, the NIF tools create a so called query mediation wrapper for the resource. The resources mapped currently include databases and datasets of a variety of information including grants, brain structures, cells, drugs, gene expression, software tools, and antibodies.  As the NIF project continues to grow, the inclusion of additional level 3 resources are anticipated.

To register a database at level 3, please contact the NIF team or recommend a resource online.

The NIF Registry is a catalog of neuroscience relevant resources that has been manually annotated using a set of descriptors to characterize the type of resource (e.g., reagent provider, software resource, database, etc.) and its biological scope (e.g., neurophysiology, Parkinson's disease, neurodevelopment, etc.). Additional information like short name and parent organization has also been provided. In general, the detailed content within the resource is not characterized. For example, if a site has MRI data on many different neurodegenerative diseases, the site will be classified under “MRI” and "neurodegenerative disease" and not all the specific types of neurodegenerative diseases it contains. The NIF Web is a customized Web index created from the core set of neuroscience-relevant resources listed in the NIF Registry. The sites from the NIF Registry are crawled, as well as the sites to which they are linked.  While not as broad as Google, NIF Web provides a more focused view that can be very useful for finding neuroscience information or resources.  Content presented on dynamically generated pages, i.e., contained in a database, will not have been indexed in NIF Web and, therefore, is inaccessible to NIF Web queries. The NIF provides access to this deep hidden content through the NIF Data Federation. Once a resource is registered to the NIF Data Federation, direct queries can be made against the database or dataset through the NIF interface.

A concept-based search is a search based on the meaning of a term rather than the literal string.  A concept-based query would allow a user to search for “cell” as part of biological organism as opposed to “cell” as a place to hold prisoners, or a type of phone.  A concept-based search is difficult without explicit mappings between terms and the NIF ontologies.  When such explicit mappings are available, NIF uses them to retrieve relevant resources.  If such mappings aren’t available, NIF still uses the NIF vocabularies to try to refine the search in a way that is more useful.  For example, NIF includes all synoyms and will allow the inclusion of related terms.  In upcoming versions of the NIF, we will use the relationships in our vocabularies to rank search results based on semantic similarity.

Although the NIF offers a concept-based search (using the formal semantics of the NIFSTD ontology), the NIF also uses a string based search in order to maximize the possibility of locating relevant resources. As mentioned above, because the concept-based search currently relies on human annotation, and because resources and vocabularies are constantly evolving, only a subset of the registered resources in the NIF have access to the concept-based query. The annotation process is also not completely straightforward, as many resource descriptions require capturing complex inter-related semantic facets, a process that is difficult to automate. For this reason, we have also implemented a standard, term-based search common in Web search engines. Though the results of such term or string-based searches cannot provide the advantages offered by concept-based searches, they do comprehensively cover the NIF’s registered resource pool. In the course of ongoing NIF development, these two forms of search will be synergistically combined to gradually increase both the conceptual accuracy and comprehensive coverage of the NIF resource repository searching.

The NIF basic vocabularies are derived from the NIF terminology workshops run by Dr. Daniel Gardner. Experts in various neuroscience domains contributed the major high-level terms that were then arranged in a shallow hierarchy, coded in XML. This coarsely specified set of controlled terms was assembled primarily to ensure the concepts used to index neuroscience resources in the NIF Registry reflected the broadest possible interests across the neuroscience community. To support fine-grained nuanced concept-driven level 3 queries, the NIF basic vocabulary was incorporated into a formal ontology (NIFSTD) constructed according to biomedical ontology best practices (OBO Foundry Principles supported by the National Center for Biomedical Ontologies), which include the re-use of relevant existing ontologies. NIFSTD re-uses the core structure of the BIRNLex, a lexicon of concepts largely covering neuroanatomy across scales, organism taxonomy, and disease, and incorporates community ontologies such as the Gene Ontology and Neuronames. BIRNLex is encoded in OWL, the Web ontology language.

The NeuroLex Wiki provides a way for the community to contribute, edit, or comment on the NIF vocabularies.  Please refer to the How to Contribute link for specific details or you may provide feedback directly to the NIF team.  If you have a terminology that covers a domain not currently represented in NIF, please consider working with the NIF to make your vocabulary available.

The NIF crawler indexes a selected number of Web sources. The crawl typically runs once a week. The crawler will obey standard robot rules and the user-agent is called NIF. If you would prefer to not be crawled by the NIF crawler, simply add the following to your robots.txt file:

User-agent: NIF
Disallow: /

The Professor Icon indicates a tutorial is available for the database or tool retrieved through a NIF search.  The tutorials show how users access a particular resource through the NIF and what functions and information are available from that resource.