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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.
http://scicrunch.org/resources
Portal providing identifiers for Antibodies, Model Organisms, and Tools (software, databases, services) created in support of the Resource Identification Initiative, which aims to promote research resource identification, discovery, and reuse. The portal offers a central location for obtaining and exploring Research Resource Identifiers (RRIDs) - persistent and unique identifiers for referencing a research resource. A critical goal of the RII is the widespread adoption of RRIDs to cite resources in the biomedical literature and other places that reference their generation or use. RRIDs use established community identifiers where they exist, and are cross-referenced in their system where more than one identifier exists for a single resource.
Proper citation: Resource Identification Portal (RRID:SCR_004098) Copy
Repository of biochemical, genetic, and structural information about DNA Polymerases. Polbase is designed to compile detailed results of polymerase experimentation, presenting them in a dynamic view to inform further research. After validation, results from references are displayed in context with relevant experimental details and are always traceable to their source publication. Polbase is connected to other resources, including PubMed, UniProt and the RCSB Protein Data Bank, to provide multi-faceted views of polymerase knowledge. In addition to a simple web interface, Polbase data is exposed for custom analysis by external software.
Proper citation: Polbase (RRID:SCR_006107) Copy
https://phenome.jax.org/centers/QTLA
Raw data from various QTL (quantitative trait loci) studies using rodent inbred line crosses. Data are available in the .csv format used by R/qtl and pseudomarker programs. In some cases analysis scripts and/or results are posted to accompany the data. These data are provided as a courtesy to the genetic mapping community and may be used for purposes of developing or testing new analysis methods or software and for meta-analysis of quantitative traits. The authors of the datasets retain individual ownership of the data. As a courtesy to the authors, please alert them in advance of any publications that result from reanalysis of these data or obtain permission prior to redistribution of data or results. In all data sets and files, the marker locations have been translated to Cox build 37 coordinates unless otherwise stated. Please consider contributing your data to the QTL Archive.
Proper citation: QTL Archive (RRID:SCR_006213) Copy
Multi-institutional supported website and database that provides access to large number of globally used lipidomics resources. Internationally led the field of lipid curation, classification, and nomenclature since 2003. Produces new open-access databases, informatics tools and lipidomics-focused training activities will be generated and made publicly available for researchers studying lipids in health and disease.
Proper citation: LIPID Metabolites And Pathways Strategy (RRID:SCR_006579) Copy
http://www.ebi.ac.uk/Tools/webservices/psicquic/registry/registry?action=STATUS
Web service with well defined methods to enable programmatic access to molecular interactions. Standard for computational access to molecular interaction data resources.
Proper citation: PSICQUIC Registry (RRID:SCR_006389) Copy
Web based gene set analysis toolkit designed for functional genomic, proteomic, and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets etc) are continuously generated. WebGestalt incorporates information from different public resources and provides a way for biologists to make sense out of gene lists. This version of WebGestalt supports eight organisms, including human, mouse, rat, worm, fly, yeast, dog, and zebrafish.
Proper citation: WebGestalt: WEB-based GEne SeT AnaLysis Toolkit (RRID:SCR_006786) Copy
Service providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.
Proper citation: InterPro (RRID:SCR_006695) Copy
http://rankprop.gs.washington.edu/svm-fold/
This web server makes predictions of family, superfamily and fold level classifications of proteins based on the Structural Classification of Proteins (SCOP) hierarchy using the Support Vector Machine (SVM) learning algorithm. SVM-FOLD detects subtle protein sequence similarities by learning from all available annotated proteins, as well as utilizing potential hits as identified by PSI-BLAST. Predictions of classes of proteins that do not have any known example with a significant pairwise PSI-BLAST E-value can still be found using SVMs.
Proper citation: SVM-fold: Protein Fold Prediction (RRID:SCR_006834) Copy
http://bio3d.colorado.edu/imod
A free, cross-platform set of image processing, modeling and display programs used for tomographic reconstruction and for 3D reconstruction of EM serial sections and optical sections. The package contains tools for assembling and aligning data within multiple types and sizes of image stacks, viewing 3-D data from any orientation, and modeling and display of the image files. IMOD 4.1.8 Is Now Available for Linux, Windows, and Mac OS X
Proper citation: IMOD (RRID:SCR_003297) Copy
The RNA modification database provides a comprehensive listing of posttranscriptionally modified nucleosides from RNA. Information provided for each nucleoside includes: the type of RNA in which it occurs and phylogenetic distribution; common chemical name and symbol; Chemical Abstracts registry number and index name; chemical structure; initial literature citations for structural characterization or occurrence, and for chemical synthesis. Both the structural diversity and extent of posttranscriptional modification in RNA is remarkable, with 107 different nucleosides presently known in all types of RNA. The discovery of new modified nucleosides as well as increasing knowledge of the array of functional roles of modification, based largely on extensive studies of tRNA, mandates a need for a comprehensive database of RNA nucleosides. The RNA Modification Database is maintained as an extension of the initial version published in mid-1994. The database consists of all RNA-derived ribonucleosides of known structure, including those from established sequence positions, as well as those detected or characterized from hydrolysates of RNA. The information provided permits access to the modified nucleoside literature through provision of both computer-searchable Chemical Abstracts registry numbers and key literature citations. This database also provides an historical record of the initial reports of occurrence, characterization and chemical synthesis of modified nucleosides from RNA. It is our judgement that the total number of RNA nucleosides listed, and the chemical structures reported, are very accurate. However, the distributions listed are in some cases a matter of concern, due primarily to the possibility of inhomogeneity of the RNA isolate and the use of methods of nucleoside identification that are not sufficiently rigorous. Reinvestigation of some of the unusual or single-report source distributions is warranted, and will likely lead to future refinements in the listings. The authors invite comments concerning new entries, errors or omissions and on the format presently used for electronic access to the database.
Proper citation: RNA Modification Database (RRID:SCR_003535) Copy
https://www.cgl.ucsf.edu/chimera/
Software tool for interactive visualization and analysis of molecular structures and related data, including density maps, supramolecular assemblies, sequence alignments, docking results, trajectories, and conformational ensembles. High-quality images and animations can be generated. Chimera includes complete documentation and several tutorials.
Proper citation: UCSF Chimera (RRID:SCR_004097) Copy
Curated, relational database containing sequence, classification, structural, functional and evolutionary information about transport systems from variety of living organisms based on IUBMB-approved transporter classification (TC) system. Descriptions, TC numbers, and examples of over 600 families of transport proteins are provided. TC system is analogous to Enzyme Commission (EC) system for classification of enzymes, except that it incorporates both functional and phylogenetic information. TCDB users may submit their own sequenced proteins and descriptions for inclusion into database. The software tools used are all freely available for download. These programs are used for analysis of Protein and DNA sequences. Programs require UNIX server to run.
Proper citation: Transporter Classification Database (RRID:SCR_004490) Copy
An integrated text mining / natural language processing system based on the Unstructured Information Management Architecture (UIMA) Framework. It allows interoperability of text mining tools and allows the creation of text mining workflows, comparison and visualization of tools. U-Compare can be launched straight from the web or downloaded. As the name implies comparison of components and workflows is a central feature of the system. U-Compare allows sets of components to be run in parallel on the same inputs and then automatically generates statistics for all possible combinations of these components. Once a workflow has been created in U-Compare it can be exported and shared with other users or used with other UIMA compatible tools and so in addition to comparison, U-Compare also functions as a general purpose workflow creation tool. It contains a repository of 50+ biomedical text mining components. These components are included in the U-Compare single-click-to-launch package, ready to use by just drag-and-drop. You can also use this repository independent from the U-Compare system. Link with Taverna It has a link with Taverna for scientific workflows, http://bioinformatics.oxfordjournals.org/content/26/19/2486.abstract, where you can use U-Compare and its workflow from within the Taverna workflow. There are two ways, the U-Compare Taverna plugin and the U-Compare command line mode as a Taverna activity. We have recently integrated it with Peter Murray-Rust''''s OSCAR for Chemistry (see http://www.nactem.ac.uk/cheta/) Web Demo: http://www.nactem.ac.uk/software/cheta/
Proper citation: U-Compare (RRID:SCR_004911) Copy
System that classifies genes by their functions, using published scientific experimental evidence and evolutionary relationships to predict function even in absence of direct experimental evidence. Orthologs view is curated orthology relationships between genes for human, mouse, rat, fish, worm, and fly., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: PANTHER (RRID:SCR_004869) Copy
http://ccb.jhu.edu/software/FLASH/
Open source software tool to merge paired-end reads from next-generation sequencing experiments. Designed to merge pairs of reads when original DNA fragments are shorter than twice length of reads. Can improve genome assemblies and transcriptome assembly by merging RNA-seq data.
Proper citation: FLASH (RRID:SCR_005531) Copy
Portal supporting the North East Bioinformatics Collaborative''s project to sequence the genome of the Little Skate. Provided is a clearinghouse for Little Skate Genome Project and other publicly available Skate and Ray (Batoidea) genome data, and tools for data visualization and analysis. Little Skate Genome Project The little skate (Leucoraja erinacea) is a chondrichthyan (cartilaginous) fish native to the east coast of North America. Elasmobranchs (Skates, Rays, and Sharks) exhibit many fundamental vertebrate characteristics, including a neural crest, jaws and teeth, an adaptive immune system, and a pressurized circulatory system. These characteristics have been exploited to promote understanding about human physiology, immunology, stem cell biology, toxicology, neurobiology and regeneration. The development of standardized experimental protocols in elasmobranchs such as L. erinacea and the spiny dogfish shark (Squalus acanthias) has further positioned these organisms as important biomedical and developmental models. Despite this distinction, the only reported chondrichthyan genome is the low coverage (1.4x) draft genome of the elephant shark (Callorhinchus milii). To close the evolutionary gaps in available elasmobranch genome sequence data, and generate critical genomic resources for future biomedical study, the genome of L. erinacea is being sequenced by the North East Bioinformatics Collaborative (NEBC). As close evolutionary relatives, the little skate sequence will facilitate studies that employ dogfish shark and other elasmobranchs as model organisms. Skate tools include the SkateBLAST and the Skate Genome Browsers: Little Skate Mitochondrion, Thorny Skate Mitochondrion, and Ocellate Spot Skate Mitochondrion.
Proper citation: SkateBase (RRID:SCR_005302) Copy
Collect, share, and distribute information about protein three-dimensional structures. It serves as a portal for the scientific community to learn about protein structures solved by SG centers, and also to contribute their expertise in annotating protein function. The premise of the TOPSAN project is that, no matter how much any individual knows about a particular protein, there are other members of the scientific community who know more about certain aspects of the same protein, and that the collective analyses from experts will be far more informative than any local group, let alone individual, could contribute. They believe that, if the members of the biological community are given the opportunity, authorship incentives, and an easy way to contribute their knowledge to the structure annotation, they would do so. Therefore, borrowing elements from successful, distributed, collaborative projects, such as Wikipedia (the free encyclopedia anyone can edit) and from other open source software development projects, TOPSAN will be a broad, collaborative effort to annotate protein structures, initially, those determined at the JCSG. They believe that the annotation of proteins solved by structural genomics consortia offers a unique opportunity to challenge the extant paradigm of how biological data is collected and distributed, and to connect structural genomics and structural biology to the entire biological research community. TOPSAN is designed to be scalable, modular and extensible. Furthermore, it is intended to be immediately useful in a simplistic way and will accommodate incremental improvements to functionality as usage becomes more sophisticated. Their annotation pages will offer the end user a combination of automatically generated as well as expert-curated annotations of protein structures. They will use available technology to increase the speed and granularity of the exchange of scientific ideas, and use incentive mechanisms that will encourage collaborative participation.
Proper citation: TOPSAN (RRID:SCR_005758) Copy
http://publications.nigms.nih.gov/multimedia/searchresults.asp?search=All
As part of its multimedia outreach, the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health -- the United States'' medical research agency -- offers audio and video podcasts and other multimedia resources that explore the exciting world of basic biomedical research.
Proper citation: NIGMS Multimedia (RRID:SCR_005712) Copy
http://publications.nigms.nih.gov/chemhealth/
Visit ChemHealthWeb for research highlights, chemist profiles, games and videos and other Web extras. The NIGMS Chemistry of Health booklet describes basic chemistry and biochemistry research that spurs a better understanding of human health.
Proper citation: ChemHealthWeb (RRID:SCR_005851) Copy
http://bioportal.bioontology.org/
Open repository of biomedical ontologies that provides access via Web browsers and Web services to ontologies. It supports ontologies in OBO format, OWL, RDF, Rich Release Format (RRF), Protege frames, and LexGrid XML. Functionality includes the ability to browse, search and visualize ontologies as well as to comment on, and create mappings for ontologies. Any registered user can submit an ontology. The NCBO Annotator and NCBO Resource Index can also be accessed via BioPortal. Additional features: * Add Reviews: rate the ontology according to several criteria and describe your experience using the ontology. * Add Mappings: submit point-to-point mappings or upload bulk mappings created with external tools. Notification of new Mappings is RSS-enabled and Mappings can be browsed via BioPortal and accessed via Web services. * NCBO Annotator: Tool that tags free text with ontology terms. NCBO uses the Annotator to generate ontology annotations, creating an ontology index of these resources accessible via the NCBO Resource Index. The Annotator can be accessed through BioPortal or directly as a Web service. The annotation workflow is based on syntactic concept recognition (using the preferred name and synonyms for terms) and on a set of semantic expansion algorithms that leverage the ontology structure (e.g., is_a relations). * NCBO Resource Index: The NCBO Resource Index is a system for ontology based annotation and indexing of biomedical data; the key functionality of this system is to enable users to locate biomedical data linked via ontology terms. A set of annotations is generated automatically, using the NCBO Annotator, and presented in BioPortal. This service uses a concept recognizer (developed by the National Center for Integrative Biomedical Informatics, University of Michigan) to produce a set of annotations and expand them using ontology is_a relations. * Web services: Documentation on all Web services and example code is available at: BioPortal Web services.
Proper citation: BioPortal (RRID:SCR_002713) Copy
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