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URL: https://neuinfo.org/mynif/search.php?q=nlx_149462&t=indexable&list=cover&nif=nlx_144509-1
Proper Citation: Integrated Auto-Extracted Annotation (RRID:SCR_005892)
Description: A virtual database that indexes both BioNOT for negation data, and the Resource Discovery Pipeline: an automated resource discovery and semi-automated type characterization with text-mining scripts that facilitate curation team efforts to discover, integrate and display new content. This virtual database currently indexes the following resources: * BioNOT, http://snake.ims.uwm.edu/bionot/index.php?searchterm=mecp2+autism&submit=Search * Resource Discovery Pipeline, http://lucene1.neuinfo.org/nif_resource/current/
Abbreviations: Integrated AEA, Auto-Extracted Annotation
Synonyms: NIF Integrated Automatically Extracted Annotation, NIF Integrated Auto. Extracted Annotation, NIF Integrated Auto-Extracted Annotation, Integrated Automatically Extracted Annotation, Integrated Auto Extracted Annotation, NIF Auto-Extracted Annotation
Resource Type: data or information resource, data set
Defining Citation: PMID:22434839
Keywords: annotation, negative data
Funding: NIH Blueprint for Neuroscience Research ; NIDA Contract HHSN271200577531C
Availability: Data are licensed by their respective owners. Use and distribution is subject to the Terms of Use by the original resource as well as the, Creative Commons Attribution License
Resource Name: Integrated Auto-Extracted Annotation
Resource ID: SCR_005892
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Source: SciCrunch Registry (RRID:SCR_005400)
Description: Interactive portal for finding and submitting biomedical resources. Resources within SciCrunch have assigned RRIDs which are used to cite resources in scientific manuscripts. SciCrunch Registry, formerly NIF Registry, provides resources catalog. Allows to add new resources. Allows edit existing resources after registration. Curators are tasked with identifying and registering resources, examining data, writing configuration files to index and display data and keeping contents current.
URL: https://rrid.site/rin/sources/SCR_005400
The NIDDK Information Network (dkNET) serves the needs of basic and clinical investigators by providing seamless access to large pools of data and research resources relevant to the mission of The National Institute of Diabetes Digestive and Kidney Diseases (NIDDK). dkNET is hosted at University of California San Diego, and is supported by NIH NIDDK grant U24DK097771.
Email: info_at_ dknet.org
