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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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Tree-Based Pipeline Optimization Tool Resource Report Resource Website 1+ mentions |
Tree-Based Pipeline Optimization Tool (RRID:SCR_017531) | TPOT | software toolkit, software resource | Software Python package to automate building of ML pipelines by combining flexible expression tree representation of pipelines with stochastic search algorithms such as genetic programming. | Automated, machine, learning, optimize, pipeline, genetic, programming | NIAID R01 AI117694 | Free, Available for download, Freely available | SCR_017532 | https://epistasislab.github.io/tpot/, https://github.com/EpistasisLab/tpot | SCR_017531 | Tree based Pipeline Optimization Tool | 2026-08-02 09:07:33 | 1 | ||||||
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Sparse Inverse Covariance Estimation for Ecological Association Inference Resource Report Resource Website 10+ mentions |
Sparse Inverse Covariance Estimation for Ecological Association Inference (RRID:SCR_022646) | SPIEC-EASI | software toolkit, software resource | Software R package estimates inverse covariance matrix from sequencing data.Statistical method for inference of microbial ecological networks from amplicon sequencing datasets. | inverse covariance matrix estimation, sequencing data, microbial ecological networks inference, amplicon sequencing datasets microbial ecological networks, | NIAID T32AI007180; NIDDK R01 DK103358; NIGMS RO1 GM63270; Simons Foundation |
PMID:25950956 | Free, Available for download, Freely available | SCR_022646 | SParse InversE Covariance Estimation for Ecological Association Inference | 2026-08-02 09:08:41 | 12 | |||||||
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SingleR Resource Report Resource Website 100+ mentions |
SingleR (RRID:SCR_023120) | software toolkit, software resource | Software R package for unbiased cell type recognition of scRNA-seq data. Performs unbiased cell type recognition from single-cell RNA sequencing data, by leveraging reference transcriptomic datasets of pure cell types to infer cell of origin of each single cell independently. | unbiased cell type recognition, scRNA-seq data, reference transcriptomic datasets, pure cell types, infer cell of origin | UCSF Marcus Award ; NHLBI HL131560; UCSF Nina Ireland Program award ; NHLBI HL139897; NIAID |
PMID:30643263 | Free, Available for download, Freely available | https://github.com/dviraran/SingleR, https://github.com/LTLA/SingleR | SCR_023120 | Single-cell RNA-seq cell types Recognition | 2026-08-02 09:08:39 | 321 | |||||||
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DADA2 Resource Report Resource Website 500+ mentions |
DADA2 (RRID:SCR_023519) | software toolkit, software resource | Open source software R package for modeling and correcting Illumina sequenced amplicon errors. Fast and accurate sample inference from amplicon data with single nucleotide resolution. | modeling and correcting amplicon errors, Illumina sequenced amplicon errors, amplicon errors, sample inference, amplicon data, single nucleotide resolution |
is used by: ImmuMicrobiome is related to: dadasnake has parent organization: Stanford University; Stanford; California |
NSF ; NIAID R01AI112401; Samarth Foundation |
PMID:27214047 | Free, Available for download, Freely available | https://bioconductor.org/packages/dada2/ | SCR_023519 | 2026-08-02 09:08:38 | 960 | |||||||
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ATHLATES Resource Report Resource Website 1+ mentions |
ATHLATES (RRID:SCR_023689) | software toolkit, software resource | Software package for determining HLA genotypes for individuals from Illumina exome sequencing data. Program applies assembly, allele identification and allelic pair inference to short read sequences, and applies it to data from Illumina platforms. | Illumina, HLA genotypes determination, Illumina exome sequencing data, allele identification, allelic pair inference, short read sequence, | Washington University School of Medicine ; NIAID ; National Institutes of Health ; Department of Health and Human Services |
PMID:23748956 | Free, Available for download, Freely available | SCR_023689 | 2026-08-02 09:08:51 | 3 | |||||||||
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Malaria Parasite Metabolic Pathways Resource Report Resource Website 10+ mentions |
Malaria Parasite Metabolic Pathways (RRID:SCR_007072) | Malaria Parasite Metabolic Pathways | image collection, data or information resource, data set | Data set of metabolic pathways for the malaria parasite based on the present knowledge of parasite biochemistry and on pathways known to occur in other unicellular eukaryotes. This site extracted the pertinent information from the universal sites and presented them in an educative and informative format. The site also includes, cell-cell interactions (cytoadherence and rosetting), invasion of the erythrocyte by the parasite and transport functions. It also contains an artistic impression of the ultrastructural morphology of the interaerythrocytic cycle stages and some details about the morphology of mitochondria and the apicoplast. Most pathways are relevant to the erythrocytic phase of the parasite cycle. All maps were checked for the presence of enzyme-coding genes as they are officially annotated in the Plasmodium genome (http://plasmodb.org/). The site is constructed in a hierarchical pattern that permits logical deepening: * Grouped pathways of major chemical components or biological process ** Specific pathways or specific process *** Chemical structures of substrates and products or process **** Names of enzymes and their genes or components of process Each map is linked to other maps thus enabling to verify the origin of a substrate or the fate of a product. Clicking on the EC number that appears next to each enzyme, connects the site to BRENDA, SWISSPROT ExPASy ENZYME, PlasmoDB and to IUBMB reaction scheme. Clicking of the name of a metabolite, connects the site to KEGG thus providing its chemical structure and formula. Next to each enzyme there is a pie that depicts the stage-dependent transcription of the enzyme''s coding gene. The pie is constructed as a clock of the 48 hours of the parasite cycle, where red signifies over-transcription and green, under-transcription. Clicking on the pie links to the DeRisi/UCSF transcriptome database. | enzyme, gene, genome, map, metabolic, mosquito, parasite, pathway, plasmodium falciparum, protein, reaction, sequence, metabolic pathway, chemical structure, cell-cell interaction, transport, morphology, mitochondria, apicoplast | has parent organization: Hebrew University of Jerusalem; Jerusalem; Israel | Malaria | UNDP/World Bank/WHO Special Programme ; NIAID ; European Union ; 6th FP- BioMalPar Network of Excellence on Biology and Pathology of the Malaria Parasite |
nif-0000-21249 | SCR_007072 | 2026-08-03 09:33:21 | 20 | |||||||
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E. coli Genome project Resource Report Resource Website 1+ mentions |
E. coli Genome project (RRID:SCR_008139) | topical portal, data or information resource, database, portal | The E. coli Genome Project has the goal of completely sequencing the E. coli and human genomes. They began isolation of an overlapping lambda clonebank of E. coli K-12 strain MG1655. Those clones served as the starting material in our initial efforts to sequence the whole genome. Improvements in sequencing technology have since reached the point where whole-genome sequencing of microbial genomes is routine, and the human genome has in fact been completed. They initiated additional sequencing efforts, concentrating on pathogenic members of the family Enterobacteriaceae -- to which E. coli belongs. They also began a systematic functional characterization of E. coli K-12 genes and their regulation, using the whole genome sequence to address how the over 4000 genes of this organism act together to enable its survival in a wide range of environments. | e. coli, enterobcteriaceae, gene, genome, human, journal aricle, knowledgebase, regulation, sequence, job | has parent organization: University of Wisconsin-Madison; Wisconsin; USA | NIAID ; NHGRI |
nif-0000-20961 | SCR_008139 | E.Coli genome project | 2026-08-03 09:33:55 | 5 | ||||||||
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Sequencing of Idd regions in the NOD mouse genome Resource Report Resource Website 1+ mentions |
Sequencing of Idd regions in the NOD mouse genome (RRID:SCR_001483) | Sequencing of Idd regions in the NOD mouse genome | resource, data or information resource, data set | Genetic variations associated with type 1 diabetes identified by sequencing regions of the non-obese diabetic (NOD) mouse genome and comparing them with the same areas of a diabetes-resistant C57BL/6J reference mouse allowing identification of single nucleotide polymorphisms (SNPs) or other genomic variations putatively associated with diabetes in mice. Finished clones from the targeted insulin-dependent diabetes (Idd) candidate regions are displayed in the NOD clone sequence section of the website, where they can be downloaded either as individual clone sequences or larger contigs that make up the accession golden path (AGP). All sequences are publicly available via the International Nucleotide Sequence Database Collaboration. Two NOD mouse BAC libraries were constructed and the BAC ends sequenced. Clones from the DIL NOD BAC library constructed by RIKEN Genomic Sciences Centre (Japan) in conjunction with the Diabetes and Inflammation Laboratory (DIL) (University of Cambridge) from the NOD/MrkTac mouse strain are designated DIL. Clones from the CHORI-29 NOD BAC library constructed by Pieter de Jong (Children's Hospital, Oakland, California, USA) from the NOD/ShiLtJ mouse strain are designated CHORI-29. All NOD mouse BAC end-sequences have been submitted to the International Nucleotide Sequence Database Consortium (INSDC), deposited in the NCBI trace archive. They have generated a clone map from these two libraries by mapping the BAC end-sequences to the latest assembly of the C57BL/6J mouse reference genome sequence. These BAC end-sequence alignments can then be visualized in the Ensembl mouse genome browser where the alignments of both NOD BAC libraries can be accessed through the Distributed Annotation System (DAS). The Mouse Genomes Project has used the Illumina platform to sequence the entire NOD/ShiLtJ genome and this should help to position unaligned BAC end-sequences to novel non-reference regions of the NOD genome. Further information about the BAC end-sequences, such as their alignment, variation data and Ensembl gene coverage, can be obtained from the NOD mouse ftp site. | genome, sequencing, genome sequencing, insulin-dependent diabetes, c57bl/6j, single nucleotide polymorphism, genetic variation, bacterial artificial chromosome, sequence, gene, animal model, clone, annotation, contig |
lists: VEGA is listed by: NIDDK Information Network (dkNET) has parent organization: Wellcome Trust Sanger Institute; Hinxton; United Kingdom |
Type 1 diabetes, Diabetes | NIAID AI 15416; NIDDK ; JDRF |
PMID:23729657 | Free, Freely available | nlx_152738 | http://www.sanger.ac.uk/resources/mouse/nod/ | SCR_001483 | Sequencing of Insulin-dependent diabetes regions in the NOD mouse genome | 2026-08-03 09:31:24 | 1 | |||
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Short Time-series Expression Miner (STEM) Resource Report Resource Website 50+ mentions |
Short Time-series Expression Miner (STEM) (RRID:SCR_005016) | STEM | software resource, software application, data processing software | The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database supporting GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible | statistical analysis, term enrichment, visualization, cluster, compare, short time series, gene expression, microarray, expression profile, gene, gene ontology, gene enrichment analyses, FASEB list |
is listed by: Gene Ontology Tools is related to: Gene Ontology has parent organization: Carnegie Mellon University; Pennsylvania; USA |
NIAID NO1 AI-5001; NSF 0448453 |
PMID:16597342 PMID:15961453 |
Open unspecified license - Free for academic use | nlx_97053 | SCR_005016 | Short Time-series Expression Miner | 2026-08-03 09:32:49 | 81 | |||||
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Dynamic Regulatory Events Miner Resource Report Resource Website 1+ mentions |
Dynamic Regulatory Events Miner (RRID:SCR_003080) | DREM | software resource, software application, data processing software | The Dynamic Regulatory Events Miner (DREM) allows one to model, analyze, and visualize transcriptional gene regulation dynamics. The method of DREM takes as input time series gene expression data and static transcription factor-gene interaction data (e.g. ChIP-chip data), and produces as output a dynamic regulatory map. The dynamic regulatory map highlights major bifurcation events in the time series expression data and transcription factors potentially responsible for them. DREM 2.0 was released and supports a number of new features including: * new static binding data for mouse, human, D. melanogaster, A. thaliana * a new and more flexible implementation of the IOHMM supports dynamic binding data for each time point or as a mix of static/dynamic TF input * expression levels of TFs can be used to improve the models learned by DREM * the motif finder DECOD can be used in conjuction with DREM and help find DNA motifs for unannotated splits * new features for the visualization of expressed TFs, dragging boxes in the model view, and switching between representations | transcription, gene regulation, dynamics, time series, gene expression, static, dynamic, transcription factor-gene interaction, chip-chip, transcription factor, regulatory network, hidden markov model, systems biology, gene regulatory network, times series expression data, dynamic network, chip-seq | has parent organization: Carnegie Mellon University; Pennsylvania; USA | NIH ; NIGMS 1RO1 GM085022; NIAID DNO1 AI-5001; NSF 0448453 |
PMID:22897824 | Free, Available for download, Freely available | nif-0000-30478 | SCR_003080 | Dynamic Regulatory Events Miner (DREM) | 2026-08-03 09:32:11 | 5 | |||||
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Ontodog: A Web-based Ontology View Generator Resource Report Resource Website 10+ mentions |
Ontodog: A Web-based Ontology View Generator (RRID:SCR_005061) | Ontodog | service resource, software resource, source code, production service resource | Ontodog is a web-based ontology view generator. It can generate inSubset annotation ontology, user preferred label annotation ontology and subset of source ontology. Simply provide Ontodog input term file (Microsoft Excel file or tab-delimited text file), select one source ontology or enter your own source ontology and SPARQL endpoint, then set the settings for Ontodog output files and get the OWL (RDF/XML) Output files. Ontodog performs the basic ontology modularization-like function, i.e.,it automatically extracts all axioms and related terms associated with user-specified signature term(s). In addition, Ontodog includes extra features: (1) extracting all instance data associated with the retrieved class terms and annotations; and (2) recursively extracting all axioms and related terms indirectly associated with signature terms. More features are being added to Ontodog, such as relabeling preferred names for various ontology terms to fit in with the needs from a specific community. The Ontodog input data requires a source ontology and a list of user-specified signature terms in tab-delimited format. Ontodog provides the template files for generating the signature terms as the input terms file to download. There are several output options that the users can choose based on their needs. With more and more ontologies being developed, Ontodog offers a timely web-based package of solutions for ontology view generation. Ontodog provides an efficient approach to promote ontology sharing and interoperability. It is easy to use and does not require knowledge of SPARQL, script programming, and command line operation. Ontodog is developed to serve the ontology community for ontology reuse. It is freely available under the Apache License 2.0. The source code is made available under Apache License 2.0. | ontology, interoperability | has parent organization: University of Michigan Medical School; Michigan; USA | Rackham Pilot Research ; NIAID R01AI081062; NIGMS 5R01GM93132-1 |
nlx_144053 | SCR_005061 | 2026-08-03 09:32:35 | 17 | ||||||||
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EASE: the Expression Analysis Systematic Explorer Resource Report Resource Website 50+ mentions |
EASE: the Expression Analysis Systematic Explorer (RRID:SCR_013361) | EASE | software resource, software application, data processing software | Windows(c) desktop software application, customizable and standalone, that facilitates the biological interpretation of gene lists derived from the results of microarray, proteomic, and SAGE experiments. Provides statistical methods for discovering enriched biological themes within gene lists, generates gene annotation tables, and enables automated linking to online analysis tools. Offers statistical models to deal with multi-test comparison problem. Platform: Windows compatible | gene, microarray, genome, gene ontology, statistical analysis, enrichment analysis, FASEB list |
is listed by: 3DVC is listed by: Gene Ontology Tools is related to: Gene Ontology has parent organization: Database for Annotation Visualization and Integrated Discovery |
NIAID | PMID:12734009 PMID:19131956 PMID:19033363 |
Free for academic use | nlx_149218 | SCR_013361 | Expression Analysis Systematic Explorer | 2026-08-03 09:35:13 | 94 | |||||
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NS-Forest Resource Report Resource Website 1+ mentions |
NS-Forest (RRID:SCR_018348) | software resource, software application, data processing software | Software tool as method that takes cluster results from single cell nuclei RNAseq experiments and generates lists of minimal markers needed to define each cell type cluster. Utilizes random forest of decision trees machine learning approach. Used to determine minimum set of marker genes whose combined expression identified cells of given type with maximum classification accuracy. | Single cell, RNAseq experiment, generated gene list, minimum set, marker gene, define cell type cluster, random forest, decision tree, machine learning, identify cell, cell clasyfication | is related to: Allen Institute for Brain Science | Allen Institute for Brain Science ; JCVI Innovation Fund ; NIAID R21 AI122100; NIAID U19 AI118626; California Institute for Regenerative Medicine ; Wellcome Trust ; Chan Zuckerberg Initiative DAF |
PMID:29590361 | Free, Available for download, Freely available | SCR_018348 | Necessary and Sufficient Forest, NS-Forestversion 1.3, NS-Forest v2.0, NS-Forest version 1.0 | 2026-08-03 09:36:56 | 2 | |||||||
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Minimum Information about Biosynthetic Gene cluster Resource Report Resource Website 50+ mentions |
Minimum Information about Biosynthetic Gene cluster (RRID:SCR_023660) | MIBiG | data or information resource, database, portal, project portal | MIBiG is genomic standards consortium project and biosynthetic gene cluster database used as reference dataset. Provides community standard for annotations and metadata on biosynthetic gene clusters and their molecular products. Standardised data format that describes minimally required information to uniquely characterise biosynthetic gene clusters. MIBiG 2.0 is expended repository for biosynthetic gene clusters of known function. MIBiG 3.0 is database update comprising large scale validation and re-annotation of existing entries and new entries. Community driven effort to annotate experimentally validated biosynthetic gene clusters. | Genomic standards consortium project, community standard, annotations and metadata standards, biosynthetic gene clusters, sequence framework, biosynthetic gene cluster data, | Netherlands Organization for Scientific Research VENI grant ; NSF CAREER Award ; UK Biotechnology and Biological Sciences Research Council ; Novo Nordisk Foundation ; NIH U41 AT008718; Danish National Research Foundation ; NCCIH U24 AT010811; NCCIH F32 AT011475; Natural Sciences and Engineering Council of Canada Discovery grant ; European Union Horizon 2020 projects CARTNET ; Horizon 2020 Marie Skłodowska-Curie ; U.S. Department of Energy ; Portuguese Science and Technology Foundation ; U.S. National Science Foundation ; National Research Foundation of Korea ; NIGMS GM134688; NIAID R01AI155694; Netherlands eScience Center Accelerating Scientific Discoveries Grant ; Funds of the Chemical Industry Germany ; UK government Department for Environment ; Food and Rural Affairs ; German Chemical Industry ; Natural Sciences and Engineering Council of Canada |
PMID:36399496 DOI:10.1093/nar/gkz882 |
Free, Freely available | SCR_023660 | MIBiG 3.0, MIBiG 2.0 | 2026-08-03 09:38:28 | 55 | |||||||
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ApiDots Resource Report Resource Website 1+ mentions |
ApiDots (RRID:SCR_001778) | data or information resource, database | Note: ApiDots is currently unavailable. For data on apicomplexan EST assemblies, please see EuPathDB ApiDots is a database integrating mRNA/EST sequences from numerous Apicomplexan parasites. ESTs and mRNAs were clustered and further assembled to generate consensus sequences. These consensus sequences were then subjected to database searches against protein sequences and protein domain sequences. The underlying relational structure of this database allows researchers to analyze these data and pose biologically interesting questions. | est, apicomplexan parasite, mrna, protein domain sequence, protein sequence |
is related to: Eukaryotic Pathogen Database Resources has parent organization: University of Pennsylvania; Philadelphia; USA |
USDA ; Amerman Family Foundation ; Merck Research Laboratories ; Burroughs Wellcome Fund ; NRI 99-35204-8615; NIAID AI45806; NIAID AI45806A1; NIAID AI48121 |
PMID:12618375 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-02556 | SCR_001778 | 2026-08-03 09:31:26 | 2 | |||||||
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HIV Molecular Immunology Database Resource Report Resource Website 1+ mentions |
HIV Molecular Immunology Database (RRID:SCR_002893) | HIV Molecular Immunology Database | data or information resource, database | An annotated, searchable collection of HIV-1 cytotoxic and helper T-cell epitopes and antibody binding sites, plus related tools and information. The goal of this database is to provide a comprehensive listing of defined HIV epitopes. These data are also printed in the HIV Molecular Immunology compendium, which is updated yearly and provided free of charge to scientific researchers, both by online download and as a printed copy. The data included in this database are extracted from the HIV immunology literature. HIV-specific B-cell and T-cell responses are summarized and annotated. Immunological responses are divided into three sections, CTL (CD8+), T helper (CD4+), and antibody. Within these sections, defined epitopes are organized by protein and binding sites within each protein, moving from left to right through the coding regions spanning the HIV genome. We include human responses to natural HIV infections, as well as vaccine studies in a range of animal models and human trials. Responses that are not specifically defined, such as responses to whole proteins or monoclonal antibody responses to discontinuous epitopes, are summarized at the end of each protein sub-section. Studies describing general HIV responses to the virus, but not to any specific protein, are included at the end of each section. The annotation includes information such as cross-reactivity, escape mutations, antibody sequence, TCR usage, functional domains that overlap with an epitope, immune response associations with rates of progression and therapy, and how specific epitopes were experimentally defined. Basic information such as HLA specificities for T-cell epitopes, isotypes of monoclonal antibodies, and epitope sequences are included whenever possible. All studies that we can find that incorporate the use of a specific monoclonal antibody are included in the entry for that antibody. A single T-cell epitope can have multiple entries, generally one entry per study. Finally, tables and maps of all defined linear epitopes relative to the HXB2 reference proteins are provided. Alignments of CTL, helper T-cell, and antibody epitopes are available through the search interfaces. Only responses to HIV-1 and HIV-2 are included in the database. | cytotoxic t cell, cytotoxic t lymphocyte, helper t-cell, antibody, binding site, epitope, t cell epitope, human immunodeficiency virus, immunology, molecule, genome, protein, alignment, b-cell, t-cell, annotation, ctl, t helper, coding region, cross-reactivity, escape mutation, antibody sequence, tcr usage, functional domain, immune response, progression, therapy | has parent organization: HIV Databases | Human immunodeficiency virus | NIAID | nif-0000-02965 | http://hiv-web.lanl.gov/immunology/ | SCR_002893 | Human Immunodeficiency Virus Molecular Immunology Database | 2026-08-03 09:31:53 | 2 | |||||
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Nonhuman Primate HIV/SIV Vaccine Trials Database Resource Report Resource Website |
Nonhuman Primate HIV/SIV Vaccine Trials Database (RRID:SCR_002274) | data or information resource, database | An overview of HIV and SIV vaccine trials and their outcomes. It was developed as a tool for compilation, search and comparison of published studies on SIV, HIV and SHIV vaccine trials in nonhuman primates. We used a set of criteria to scan Pubmed for relevant studies to enter into the database. In selecting studies for entry, priority was given to recently published studies in journals generally regarded as the primary source of information pertaining to HIV and SIV vaccine research in nonhuman primates. In most cases, we give priority to challenge studies, where the animals received a live virus to measure the "efficacy" of the immunogen(s) inoculated during the course of the investigation. The HIV Sequence Database focuses on five primary goals: *Collecting HIV and SIV sequence data (all sequences since 1987) *Curating and annotating this data, and making it available to the scientific community *Computer analysis of HIV and related sequences *Production of software for the analysis of (sequence) data *Publication of the data and analyses on this site and in a yearly printed publication, the HIV sequence Compendium, which is available free of charge | drug, trial, vaccine, human immunodeficiency virus, simian immunodeficiency virus | has parent organization: HIV Databases | Human immunodeficiency virus, Simian immunodeficiency virus | NIAID | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-20999 | http://hiv-web.lanl.gov/cgi-bin/vaccine/public/index.cgi | SCR_002274 | HIV/SIV Trials Vaccine DB, HIV/SIV Trials Vaccine Database | 2026-08-03 09:31:51 | 0 | |||||
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National Swine Resource and Research Center Resource Report Resource Website 50+ mentions |
National Swine Resource and Research Center (RRID:SCR_006855) | NSRRC | cell repository, biomaterial supply resource, material resource, organism supplier | Provides access to critically needed swine models of human health and disease as well as a central resource for reagents, creation of new genetically modified swine, and information and training related to use of swine models in biomedical research. | RIN, Resource Information Network, pig, fetal fibroblast, live animal, tissue, fibroblast, fetus, genetically modified pig, biomaterial manufacture, genome, genotyping, genetics, reproduction, breeding, health monitoring, cryopreservation, phenotyping, consulting, RRID Community Authority |
is used by: Integrated Animals is listed by: One Mind Biospecimen Bank Listing is listed by: Resource Information Network is related to: One Mind Biospecimen Bank Listing has parent organization: University of Missouri; Missouri; USA |
NIH Office of the Director U42 OD011140; NIAID ; NHLBI |
Public, To investigators, Application required | nif-0000-12086 | SCR_006855 | National Swine Resource Research Center | 2026-08-03 09:33:11 | 79 | ||||||
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BioDepot-workflow-builder Resource Report Resource Website 1+ mentions |
BioDepot-workflow-builder (RRID:SCR_017402) | Bwb | workflow software, software resource, software application, data processing software | Software tool to create and execute reproducible bioinformatics workflows using drag and drop interface. Graphical widgets represent Docker containers executing modular task. Widgets are linked graphically to build bioinformatics workflows that can be reproducibly deployed across different local and cloud platforms. Each widget contains form-based user interface to facilitate parameter entry and console to display intermediate results. | bioinformatics, big, data, workflow, reproducible, Docker | NIGMS R01 GM126019; NHLBI U54 HL127624; NHGRI U24HG012674; NIAID R03AI159286 |
DOI:10.1016/j.cels.2019.08.007 | Free, Available for download, Freely available | SCR_017402 | 2026-08-03 09:37:03 | 1 | ||||||||
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celltrackR Resource Report Resource Website 1+ mentions |
celltrackR (RRID:SCR_021021) | software toolkit, software application, data processing software, data analysis software, software resource | Software R package to analyze immune cell migration data. Supports pipeline for track analysis by providing methods for data management, quality control, extracting and visualizing migration statistics, clustering tracks, and simulating cell migration.Available measures include displacement, confinement ratio, autocorrelation, straightness, turning angle, and fractal dimension. Measures can be applied to entire tracks, steps, or subtracks with varying length. | Immune cell migration data, dimensional space, cell analysis, cell migration, cell tracks, cell migration data, displacement, confinement ratio, autocorrelation, turning angle, fractal dimension | is listed by: CRAN | NIAID U01 AI095550; NIAID R01 AI077600 |
DOI:10.1101/670505v1 | Free, Available for download, Freely available | https://github.com/ingewortel/celltrackR | SCR_021021 | 2026-08-03 09:37:15 | 7 |
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