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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

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On page 6 showing 101 ~ 120 out of 155 results
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  • RRID:SCR_023871

    This resource has 1+ mentions.

https://rdrr.io/cran/DrInsight/src/R/drug.identification.R

Software connectivity mapping based drug repurposing tool that identifies drugs that can potentially reverse query disease phenotype or have similar functions with query drugs.

Proper citation: DrInsight (RRID:SCR_023871) Copy   


  • RRID:SCR_024713

    This resource has 1+ mentions.

https://masst.gnps2.org/microbemasst/

Web taxonomically informed mass spectrometry search tool, tackles limited microbial metabolite annotation in untargeted metabolomics experiments. Leveraging database of over 60,000 microbial monocultures, users can search known and unknown MS/MS spectra and link them to their respective microbial producers via MS/MS fragmentation patterns.

Proper citation: microbeMASST (RRID:SCR_024713) Copy   


https://www.sanger.ac.uk/collaboration/sequencing-idd-regions-nod-mouse-genome/

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.

Proper citation: Sequencing of Idd regions in the NOD mouse genome (RRID:SCR_001483) Copy   


http://ontodog.hegroup.org/index.php

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.

Proper citation: Ontodog: A Web-based Ontology View Generator (RRID:SCR_005061) Copy   


  • RRID:SCR_016270

    This resource has 1+ mentions.

https://cedar.metadatacenter.org/

Web application for creating, collecting, testing, and sharing metadata. It provides templates for metadata models or structures, and is capable of testing those models quickly using real data.

Proper citation: CEDAR Workbench (RRID:SCR_016270) Copy   


http://www.nitrc.org/projects/ap_seg_2013_nih/

A MATLAB GUI for segmenting and quantifying PET images with multi-focal and diffuse uptakes. It imports a PET image and allows the user to draw region of interests (ROIs) in 2D or 3D to roughly separate the object of interest from the background. The areas are then segmented using a PET image segmentation method based on Affinity Propagation clustering to cluster the image intensities into meaningful groups. For quantification, the Standardized Uptake Value measurements of the binary or the user defined ROI are SUVmax, SUVmean, and Volume (mm^3) and can be exported into an excel sheet.

Proper citation: NIH-CIDI Segmentation of PET Images based on Affinity Propagation Clustering (RRID:SCR_014151) Copy   


https://www.rdocumentation.org/packages/DGCA/versions/1.0.2

Software R package to perform differential gene correlation analysis. Performs differential correlation analysis on input matrices, with multiple conditions specified by design matrix.

Proper citation: Differential Gene Correlation Analysis (RRID:SCR_020964) Copy   


  • RRID:SCR_021021

    This resource has 1+ mentions.

https://cran.r-project.org/web/packages/celltrackR/index.html

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.

Proper citation: celltrackR (RRID:SCR_021021) Copy   


  • RRID:SCR_010508

    This resource has 10+ mentions.

https://www.immunespace.org/

A consortium of university groups to characterize human immune populations. The Human Immunology Project Consortium (HIPC) program, established in 2010 by the NIAID Division of Allergy, Immunology, and Transplantation, is a major collaborative effort that is generating large amounts of cross-center and cross-assay data including high-dimensional data to characterize the status of the immune system in diverse populations under both normal conditions and in response to stimuli. This large data problem has given birth to ImmuneSpace, a powerful data management and analysis engine where datasets can be easily explored and analyzed using state-of-the-art computational tools.

Proper citation: ImmuneSpace (RRID:SCR_010508) Copy   


https://mibig.secondarymetabolites.org/

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.

Proper citation: Minimum Information about Biosynthetic Gene cluster (RRID:SCR_023660) Copy   


http://web.cbio.uct.ac.za/~darren/rdp.html

Software package to analyse nucleotide sequence data and identify evidence of genetic recombination. RDP3 is version of RDP program for characterizing recombination events in DNA-sequence alignments. RDP4 is version of RDP program for detection and analysis of recombination patterns in virus genomes.

Proper citation: Recombination Detection Program (RRID:SCR_018537) Copy   


  • RRID:SCR_019121

    This resource has 1000+ mentions.

https://bioweb.pasteur.fr/packages/pack@[email protected]

Open source software tool for analysing trace files generated by Bayesian MCMC runs. Software package for visualising and analysing MCMC trace files generated through Bayesian phylogenetic inference. Provides kernel density estimation, multivariate visualisation, demographic trajectory reconstruction, conditional posterior distribution summary and more.

Proper citation: Tracer (RRID:SCR_019121) Copy   


  • RRID:SCR_019236

https://github.com/datatagsuite

Software suite to enable discoverability of datasets. Enables submission of metadata on datasets to DataMed. Has core set of elements, which are generic and applicable to any type of dataset, and extended set that can accommodate more specialized data types. Platform independent model developed by NIH BD2K bioCADDIE project for DataMed Data Discovery Index prototype being developed. Also available as annotated serialization in schema.org, which in turn is widely used by major search engines like Google, Microsoft, Yahoo and Yandex.

Proper citation: DatA Tag Suite (RRID:SCR_019236) Copy   


  • RRID:SCR_020982

    This resource has 100+ mentions.

https://www.archrproject.com/

Software R package for processing and analyzing single-cell ATAC-seq data. Used for integrative single cell chromatin accessibility analysis.Provides intuitive, user focused interface for complex single cell analysis, including doublet removal, single cell clustering and cell type identification, unified peak set generation, cellular trajectory identification, DNA element-to-gene linkage, transcription factor footprinting, mRNA expression level prediction from chromatin accessibility and multi-omic integration with single-cell RNA sequencing.

Proper citation: ArchR (RRID:SCR_020982) Copy   


  • RRID:SCR_001881

    This resource has 10000+ mentions.

https://david.ncifcrf.gov/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025. Bioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.

Proper citation: DAVID (RRID:SCR_001881) Copy   


  • RRID:SCR_000614

    This resource has 100+ mentions.

http://www.hiv.lanl.gov/content/index

Contains comprehensive data on HIV genetic sequences and immunological epitopes. This collection of databases contains tools to visualize and analyze HIV-related data.

Proper citation: HIV Databases (RRID:SCR_000614) Copy   


http://www.immuneprofiling.org/

Consortium established to capitalize on recent advances in immune profiling methods in order to create a novel public resource that characterizes diverse states of the human immune system following infection; prior to and following vaccination against an infectious disease; or prior to and following treatment with an immune adjuvant that targets a known innate immune receptor(s). Through this program, well-characterized human cohorts are studied using a variety of modern analytic tools, including multiplex transcriptional, cytokine, and proteomic assays; multiparameter phenotyping of leukocyte subsets; assessment of leukocyte functional status; and multiple computational methods. Centralized research resources and a comprehensive, centralized database will be constructed for use by the greater scientific community. The information gained from the program will provide a comprehensive understanding of the human immune system and its regulation, and will reveal novel associations between components of the immune system and other biological systems, identify novel immune mediators and pathways, establish predictors of vaccine safety in different populations, and enable the rapid evaluation of different vaccine formulations and administration regimens in human populations.

Proper citation: Human Immunology Project Consortium (RRID:SCR_001491) Copy   


  • RRID:SCR_006019

    This resource has 10+ mentions.

http://hcv.lanl.gov/content/sequence/HCV/ToolsOutline.html

The HCV sequence database collects and annotates sequence data and provides them to the public via a website that contains a user-friendly search interface and a large number of sequence analysis tools, based on the model of the highly regarded Los Alamos HIV database. The hepatitis C virus (HCV) is a significant threat to public health worldwide. The virus is highly variable and evolves rapidly, making it an elusive target for the immune system and for vaccine and drug design. At present, some 30 000 HCV sequences have been published. This central website provides annotated sequences and analysis tools that will be helpful to HCV scientists worldwide. Things you can do: * Find sequences in the database * Download sequences from the database * Retrieve data about the sequences * Analyze sequences * Work with the sequences using our tools * Download ready-made alignments The HCV sequence database was officially launched in September 2003. Since then, its usage has steadily increased and is now at an average of approximately 280 visits per day from distinct IP addresses.

Proper citation: HCV Sequence Database (RRID:SCR_006019) Copy   


  • RRID:SCR_006321

    This resource has 50+ mentions.

http://www.ontobee.org/

Web-based linked data server and browser specifically designed for ontology terms, it supports ontology visualization, query, and development. Ontobee provides a web interface for displaying the details and hierarchy of a specific ontology term. Meanwhile, Ontobee provides a RDF source code for the particular web page, which supports remote query of the ontology term and the Semantic Web. Ontobee provides an efficient and publicly available method to promote ontology sharing, interoperability, and data integration.

Proper citation: Ontobee (RRID:SCR_006321) Copy   


  • RRID:SCR_026446

    This resource has 50+ mentions.

https://github.com/dviraran/xCell

Software R package for generating cell type scores and R scripts for development of xCell. Web tool that performs cell type enrichment analysis from gene expression data for immune and stroma cell types. Used for Cell types enrichment analysis.

Proper citation: xCell (RRID:SCR_026446) Copy   



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