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https://github.com/epistasislab/hibachi
Software tool that creates data sets with particular characteristics. Method and open source software for simulating complex biological and biomedical data to aid in comparing and evaluating machine learning methods.
Proper citation: Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (RRID:SCR_017140) Copy
http://purl.bioontology.org/ontology/EDDA
Ontology terms useful for machine learning experiments. The terminology appearing in JMLA has been enriched with terms from MeSH and Emtree, the controlled vocabularies for MEDLINE and Embase, respectively. Synonyms include American and British variants and some inverted terms.
Proper citation: EDDA Study Design Terminology (RRID:SCR_010312) Copy
Web tool to predict order and disorder from amino acid sequence. Used to predict of natural disordered regions in proteins.
Proper citation: PONDR (RRID:SCR_023691) Copy
https://github.com/lanagarmire/lilikoi
Software tool as an R package for personalized pathway-based classification modeling using metabolomics data. Provides personalized pathway deregulation measurements (PDS scores) and offers a standardized classification model for biomarker prediction.
Proper citation: lilikoi (RRID:SCR_016361) Copy
http://hanalyzer.sourceforge.net/
An open-source data integration system designed to assist biologists in explaining the results observed in genome-scale experiments as well as generating new hypotheses. It combines information extraction techniques, semantic data integration, and reasoning and facilitates network visualization. The Hanalyzer source code and binaries are available for download.
Proper citation: Hanalyzer (RRID:SCR_000923) Copy
http://toxnet.nlm.nih.gov/cgi-bin/sis/htmlgen?DARTETIC
Bibliographic database providing references to developmental and reproductive toxicology literature on the National Library of Medicine's Toxicology Data Network. It covers teratology and other aspects of developmental and reproductive toxicology. It contains over 200,000 references to literature published since 1965. DART/ETIC is easily accessible and free of charge. Search by subject terms, title words, chemical name, Chemical Abstracts Service Registry Number (RN), and author. Search results can easily be viewed, printed or downloaded. Search results are displayed in relevancy ranked order, but may be sorted by publication date, author or title.
Proper citation: Developmental and Reproductive Toxicology Database (RRID:SCR_002326) Copy
http://www.ncbi.nlm.nih.gov/proteinclusters
Database of related protein sequences (clusters) consisting of proteins derived from the annotations of whole genomes, organelles and plasmids. It currently limited to Archaea, Bacteria, Plants, Fungi, Protozoans, and Viruses. It contains annotation information, publications, domains, structures, and external links and analysis tools including multiple alignments, phylogenetic trees, and genomic neighborhoods (ProtMap). Data is available for download via Protein Clusters FTP
Proper citation: Protein Clusters (RRID:SCR_003459) Copy
Transcription factor target database. Platform consolidating both computationally predicted and experimentally validated binding sites between transfer RNA-derived fragments and target genes or transcripts across multiple organisms.
Proper citation: tTFtarget (RRID:SCR_025631) Copy
https://github.com/slowkoni/rfmix
Software tool for local ancestry and admixture inference. Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference.
Proper citation: RFMix (RRID:SCR_027030) Copy
https://cdemapper.clinicalnlp.org/
Software Common Data Elements (CDEs) mapping tool to bridge the gap between local data elements and National Institutes of Health (NIH) CDEs. Elasticsearch and Large Language Model (LLM)-powered mapping tool designed for biomedical and clinical researchers to efficiently map study variables to the NIH Common Data Elements (CDEs). It integrates essential and advanced services into a user-centered mapping workflow, allowing users to choose different mapping strategies based on their project's needs.Used for enhancing National Institutes of Health common data element use with large language models.
Proper citation: CDEMapper (RRID:SCR_027602) Copy
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Welcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
