The SKR Project was initiated at NLM in order to develop programs to provide usable semantic representation of biomedical free text by building on resources currently available at the library. The SKR project is concerned with reliable and effective management of the information encoded in natural language texts. The project develops programs that provide usable semantic representation of biomedical text by building on resources currently available at the Library, especially the UMLS knowledge sources and the natural language processing tools provided by the SPECIALIST system. This Java-based API to the Semantic Knowledge Representation (SKR) Scheduler facility was created to provide users with the ability to programmatically submit jobs to the Scheduler Batch and Interactive facilities instead of using the Web-based interface.

Implementation of the Metaschema modeling language in Java, providing support for Java code, schema, and documentation generation based on one or more Metaschema model definitions.Code is developed in Java and shared via GitHub's USNISTGOV organization.

Meta learning with LLM: supplemental code for reproducibility of computational results for MLT and MLT-plus-TM. Related research paper: "META LEARNING WITH LANGUAGE MODELS: CHALLENGES AND OPPORTUNITIES IN THE CLASSIFICATION OF IMBALANCED TEXT", A. Vassilev, H. Jin, M. Hasan, 2023 (to appear on arXiv).All code and data is contained in the zip archive arxiv2023.zip, subject to the licensing terms shown below. See the Readme.txt contained there for detailed explanation how to unpack and run the code. See also requirements.txt for the necessary depedencies (libraries needed). This is not a dataset, but only python source code.

RxNorm provides normalized names for clinical drugs and links its names to many of the drug vocabularies commonly used in pharmacy management and drug interaction software, including those of First Databank, Micromedex, Gold Standard, and Multum. By providing links between these vocabularies, RxNorm can mediate messages between systems not using the same software and vocabulary. Technical documentation at http://www.nlm.nih.gov/research/umls/rxnorm/docs/index.html

Dataset includes the SRA accessions of the sequencing data used to benchmark the MetaCompare 2.0 pipeline as well as tables of bacterial taxa and antibiotic resistance genes used to perform the risk assessments. A link to the GitHub page where the pipeline source code can be found is also provided. This dataset is associated with the following publication: Rumi, M., M. Oh, B. Davis, C. Brown, J. Adeesh, P. Vikesland, A. Pruden, and L. Zhang. MetaCompare 2.0: Differential ranking of ecological and human health resistome risks. FEMS Microbiology Ecology. Oxford University Press, OXFORD, UK, 100(12): fiae155, (2024).

This code repository contains the "back-end" of the Nexus Microscopy Facility Laboratory Information Management System (NexusLIMS), developed by the NIST Office of Data and Informatics. Its primary function is to build XML-formatted research experiment records by combining metadata from many different sources (reservation systems, the collected data files, a session logger, etc.). These records are structured according to the "Nexus Experiment" schema, meaning they can be loaded into a repository and used for structured data queries.

This code repository contains the "back-end" of the Nexus Microscopy Facility Laboratory Information Management System (NexusLIMS), developed by the NIST Office of Data and Informatics. Its primary function is to build XML-formatted research experiment records by combining metadata from many different sources (reservation systems, the collected data files, a session logger, etc.). These records are structured according to the "Nexus Experiment" schema, meaning they can be loaded into a repository and used for structured data queries.

A set of hierarchical taxonomies used to categorize technology products.

The UMLS integrates and distributes key terminology, classification and coding standards, and associated resources to promote creation of more effective and interoperable biomedical information systems and services, including electronic health records.