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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
http://www.ncbi.nlm.nih.gov/bioproject
Database of biological data related to a single initiative, originating from a single organization or from a consortium. A BioProject record provides users a single place to find links to the diverse data types generated for that project. It is a searchable collection of complete and incomplete (in-progress) large-scale sequencing, assembly, annotation, and mapping projects for cellular organisms. Submissions are supported by a web-based Submission Portal. The database facilitates organization and classification of project data submitted to NCBI, EBI and DDBJ databases that captures descriptive information about research projects that result in high volume submissions to archival databases, ties together related data across multiple archives and serves as a central portal by which to inform users of data availability. BioProject records link to corresponding data stored in archival repositories. The BioProject resource is a redesigned, expanded, replacement of the NCBI Genome Project resource. The redesign adds tracking of several data elements including more precise information about a project''''s scope, material, and objectives. Genome Project identifiers are retained in the BioProject as the ID value for a record, and an Accession number has been added. Database content is exchanged with other members of the International Nucleotide Sequence Database Collaboration (INSDC). BioProject is accessible via FTP.
Proper citation: NCBI BioProject (RRID:SCR_004801) Copy
http://ccb.jhu.edu/software/glimmerhmm/
A gene finder based on a Generalized Hidden Markov Model (GHMM). Although the gene finder conforms to the overall mathematical framework of a GHMM, additionally it incorporates splice site models adapted from the GeneSplicer program and a decision tree adapted from GlimmerM. It also utilizes Interpolated Markov Models for the coding and noncoding models . Currently, GlimmerHMM's GHMM structure includes introns of each phase, intergenic regions, and four types of exons (initial, internal, final, and single).
Proper citation: GlimmerHMM (RRID:SCR_002654) Copy
https://www.vumc.org/cpm/center-precision-medicine-blog/medi-ensemble-medication-indication-resource
Medication indication software for primary and secondary uses of electronic medical record (EMR) data. MEDI was created based on multiple commonly used medication resources (RxNorm, MedlinePlus, SIDER 2, and Wikipedia ) and by leveraging both ontology and natural language processing (NLP) techniques.
Proper citation: MEDI (RRID:SCR_015668) Copy
Program to map biomedical text to the UMLS Metathesaurus and to discover Metathesaurus concepts referred to in text based on symbolic, natural-language processing and computational-linguistic techniques.
Proper citation: MetaMap (RRID:SCR_015031) Copy
http://amp.pharm.mssm.edu/X2K/
Software tool to produce inferred networks of transcription factors, proteins, and kinases predicted to regulate the expression of the inputted gene list by combining transcription factor enrichment analysis, protein-protein interaction network expansion, with kinase enrichment analysis. It provides the results as tables and interactive vector graphic figures.
Proper citation: eXpression2Kinases (RRID:SCR_016307) 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
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://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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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.
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