About NIF Search


  1. Levels of Access: NIF provides the ability to issue queries across all of its information sources through a single interface. The NIF provides different levels of access to individual resources, depending upon the type of resource and the willingness of the resource provider to register the resource and its content to the NIF. Please visit, Registering Resources to the NIF (http://neuinfo.org/registering_resources.shtm) for a description of the resource levels, or contact Anita Bandrowski at curation@neuinfo.org.

  2. Simple vs. Advanced Interfaces: As searching diverse resources and making the search results intelligible is a major challenge, we would appreciate your feedback on our search interfaces, both simple and advanced.

    1. Simple: The simple interface is a simple keyword interface, similar to many search engines. Enclosing the search terms in quotes will search for the exact phrase. Through the simple interface, users perform keyword queries.  If the keywords are part of the NIF vocabularies, they will be automatically enhanced with synonyms and abbreviations (see below). The search results are grouped according to resource type, and can be accessed by clicking through the tabs:

      1. NIF Web: A customized web index built from neuroscience relevant sites registered to the NIF, this resource offers a focused view for finding neuroscience information or resources and provides logical groupings of web results.

      2. NIF Registry: A manually curated catalog of neuroscience related resources added to the NIF. Each resource includes resource name, url, description, and resource type, with links to the resource’s full record containing additional information.

      3. NIF Data Federation: A collection of databases or datasets registered to the NIF Data Federation whose contents may be simultaneously queried. The resource results are displayed through a single interface, and are categorized by data type and nervous system level. Once a resource is selected, a brief description and type of data it contains is provided along with links to each pertinent record in the database.

      4. NIF Literature: NIF provides simultaneous search across two literature indices: PubMed and the Textpresso for Neuroscience literature corpus. Textpresso for Neuroscience is assembled from indexing a core set of neuroscience journals and articles culled from keyword searches of PubMed for neuroscience-related terms. Additionally, it is able to search the full text of research papers, not just the abstract, compared to PubMed who has a more limited search of article content. This may help to identify information within articles that may not be available to PubMed. Search results may be viewed in PubMed or within the Textpresso for Neuroscience interface. Through the Textpresso interface the user may further refine searches through the use of categories (e.g. brain region) and filters. See NIF Literature (http://neuinfo.org/nif_tools/literature_corpus.shtm) for more information on using Textpresso for Neuroscience.

    2. Advanced: The NIF utilizes many advanced features for information retrieval and integration. Chief among these is the use of a shared vocabulary for describing and querying resources. The NIF vocabularies currently consist of over 20,000 concepts derived from community ontologies and vocabularies, and enhanced through the input of neuroscience experts. The advanced interface lets a user compose a search by using the NIF vocabularies to include related terms such as super- and sub-classes and "part of" relationships.

  3. String-based vs. Concept-based searches: The NIF has taken two different approaches for searching the NIF resources: string-based and concept-based queries.

    1. String-based Search: The string-based search searches for text strings, similar to most existing search engines; however, this string-based search does take advantage of the NIF vocabularies to find synonyms, thereby enhancing its utility. String-based searches do not rely on any special annotation of the resource and provide broad query capability. Unfortunately, like most string-based search methods, it is subject to certain types of errors, e.g., it cannot distinguish between nucleus as part of a cell and nucleus as part of the brain.

    2. Concept-based Search: The concept-based search searches not for a particular text string, but for concepts. It relies on the annotation of terms in the NIF with unique identifiers from the NIF ontology. Because it does not rely on a particular string but rather on the meaning of a term, this type of search is called "concept-based." In the above example, nucleus as part of cell and nucleus as part of brain each map to a different unique identifier. The concept-based search is very powerful, but because it relies on annotation that is largely carried out by human annotators at this time, the amount of information that is available is small relative to the string-based searches.

  4. Utilizing the NIF vocabularies: The NIF vocabularies are currently organized into class hierarchies, where each concept may have one parent (i.e., superclass), one or more children (subclasses) and multiple siblings (other subclasses). Each term includes a human readable definition, synonyms, abbreviations and lexical variants. When composing a search, users can take advantage of the NIF vocabularies by including parents, children and "part of" relationships, e.g., cerebellum is part of brain, in order to enhance the likelihood of finding relevant results. When using the NIF vocabulary operations, the NIF treats compound terms as a single concept, i.e., the search is launched for "Alzheimer’s disease" rather than "Alzheimer’s" or "disease."

  5. General Query functions: The NIF search interface (from the results page) allows the user to refine both simple and advanced searches by selecting operations from the "Search" button pull-down menu.

    1. AND my terms/OR my terms: By default, terms that are entered in the Search field without quotation marks are joined by an "AND" (e.g., synuclein AND cerebellum), and will require both terms to be present to retrieve a result. You may specify that they be joined by an "OR" from the Search button pull-down menu, which will require only one of the search terms to be present to retrieve a result (e.g., synuclein OR cerebellum)

    2. Synonyms/No Synonyms: Included by default are any synonyms available in the NIF vocabularies. You may specify that they not be included from the Search button pull-down menu by clicking on the check box next to synonyms, thereby deselecting it.

  6. Advanced query functions: If the search terms are in the vocabularies, i.e., auto-completed (requires 4 letters), NIF’s advanced search interface allows the user to find related terms by clicking on Expand.

    1. Expand: Use the "Expand" button pull-down menu to expand part, or expand subclass. By default, fewer terms are retrieved (Less) for Expanded part and Expanded subclass, but you may specify to include more terms by selecting "More" from the pull-down menu.

    By default, the NIF will use the "OR" condition to search for parents, children and synonyms of a single term, e.g., if the "include NIF synonyms" function is selected for "Alzheimer’s disease", NIF will search for "Alzheimer’s disease OR Alzheimer dementia OR Alzheimer Senile Dementia OR Alzheimer Type Dementia, etc.".

    If a second term is added, NIF will use either the OR or AND condition to combine the terms, depending on which is selected.

  7. Search for Genes: To search for genes, type in "gene:" followed by the gene symbol or gene name. Example: Gene:snca. To search for an exact phrase, or make use of the Advanced Search options, use quotation marks around the term or phrase following "gene:", e.g., gene:"dopamine receptor".

*Refer to Search Tips for additional information.

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