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http://www.mugen-noe.org/database/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. MUGEN Mouse Database (MMdb) is a virtual and fully searchable repository of murine models of immune processes and immunological diseases. MMdb is being developed within the context of the MUGEN network of Excellence, a consortium of 21 leading research institutes and universities, and currently holds all mutant mouse models that were developed within the consortium. Its primary aim is to enable information exchange between participating institutions on mouse strain characteristics and availability. More importantly, it aims to create a mouse-centric international forum on modelling of immunological diseases and pave the way to systems biology of the mouse by correlating various genotypic and phenotypic characteristics. The basic categorization of models is based on three major research application categories: * Model of Human Disease * Model of Immune Processes * Transgenic Tool Mutant strains carry detailed information on affected gene(s), mutant alleles and genetic background (DNA origin, targeted, host and backcrossing background). Each gene/transgene index also includes IDs and direct links to Ensembl (EBI��s genome browser), ArrayExpress (providing expression profiles), Eurexpress II (for embryonic expression patterns) and NCBI��s Entrez Gene database. Phenotypic description is standardized and hierarchically structured, based on MGI��s mammalian phenotypic ontology terms, but also includes relevant images and references. Since version 2.1.0 MMdb is also utilizing PATO. Availability (in the form of live mice, cryopreserved embryos or sperm, as well as ES cells) is clearly indicated, along with handling and genotyping details (in the form of documents or hyperlinks) and all relevant contact information (including EMMA and JAX hyperlinks where available).

Proper citation: MUGEN Mouse Database (RRID:SCR_003243) Copy   

•   Source: SciCrunch Registry

http://childes.talkbank.org/

Child language component of TalkBank system. TalkBank is system for sharing and studying conversational interactions. Includes software developed for speech recognition and analysis as well as behavior recognition. Database contains transcript and media data collected from conversations between young children and their playmates and caretakers. Conversations with older children and adults are available from TalkBank. All of data is transcribed in CHAT and CA/CHAT formats.

Proper citation: Child Language Data Exchange System (CHILDES) (RRID:SCR_003241) Copy   

•   Source: SciCrunch Registry

http://isps.yale.edu/research/data

Data archive to assist in the sharing of research grade information pertaining to the social and economic sciences. The majority of digital content currently consists of social science research data from experiments, program files with the code for analyzing the data, requisite documentation to use and understand the data, and associated files. Access to the ISPS Data Archive is provided at no cost and is granted for scholarship and research purposes only. When possible, Data is linked to Projects and Publications, via the ISPS KnowledgeBase. ISPS operates in accordance with the prevailing standards and practices of the digital preservation community including the Open Archival Information System (OAIS) Reference Model (ISO 14721:2003) and the Data Documentation Initiative (DDI) standard. Accordingly, ISPS supports digital life-cycle management, interoperability, and preferred methods of preservation. The ISPS Data Archive is intended for use by social science researchers, policy-makers, and practitioners who are conducting or analyzing field (and other) experiments in various social science disciplines. Currently, Replication Files originate with ISPS-affiliated scholars.

Proper citation: ISPS Data Archive (RRID:SCR_003127) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics.nl/cgi-bin/primer3plus/primer3plus.cgi

A web interface to the Primer3 primer design program as an enhanced alternative for the CGI- scripts that come with Primer3.

Proper citation: Primer3Plus (RRID:SCR_003081) Copy   

•   Source: SciCrunch Registry

http://www.neuroml.org/

A XML-based description language that provides a common data format for defining and exchanging descriptions of neuronal cell and network models. It facilitates the exchange of complex neural models, allows for greater transparency and accessibility of models, enhances interoperability between simulators and other tools, and supports the development of new software and databases. Exchange of network models will aid the investigation of structure-function relationships in neuroscience including theoretical studies relating connectivity patterns to normal and neurodegenerative network states. NeuroML is a free and open community effort developed with input from many contributors. They will need your help as the standards and tools continue to evolve.

Proper citation: NeuroML (RRID:SCR_003083) Copy   

•   Source: SciCrunch Registry

https://www.ddbj.nig.ac.jp/jga/index-e.html

A service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The JGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the JGA. Once processed, all data are encrypted. The JGA accepts only de-identified data approved by JST-NBDC. The JGA implements access-granting policy whereby the decisions of who will be granted access to the data resides with the JST-NBDC. After data submission the JGA team will process the data into databases and archive the original data files. The accepted data types include manufacturer-specific raw data formats from the array-based and new sequencing platforms. The processed data such as the genotype and structural variants or any summary level statistical analyses from the original study authors are stored in databases. The JGA also accepts and distributes any phenotype data associated with the samples. For other human biological data, please contact the NBDC human data ethical committee.

Proper citation: Japanese Genotype-phenotype Archive (JGA) (RRID:SCR_003118) Copy   

•   Source: SciCrunch Registry

http://www.elsevier.com/online-tools/pathway-studio/biological-database

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. MedScan is a fast and flexible biomedical information extraction technology. It uses dictionaries to identify individual biomedical terms (proteins, cellular processes, small molecules, diseases, etc) referred to in literature articles, and applies advanced natural language processing techniques to detect the relationships within the article and extract these terms and the relationships; the overall process of detection, identification, extraction and assembling, is termed Information Harvesting. Information extracted by MedScan represents the multiple aspects of protein function, including protein modification, cellular localization, protein-protein interactions, gene expression regulation, molecular transport and synthesis, as well as association with diseases, and regulation of various cellular processes. This scope can be broadened by modifying information extraction rules and the dictionaries. Dictionaries can be assembled on any topic or area that is represented in the literature you wish to harvest. High-throughput data generation methodologies like microarray gene expression require new approaches for gathering information for data analysis. For the best results, computational approaches used for high-throughput data analysis require that biological information from the literature be a coherent and integrated part of the analysis software itself. Pathway Studio meets this challenge through its MedScan Technology and underlying ResNet database. All editions of Pathway Studio contain MedScan Technology to harvest information from the literature and to save this information in the Pathway Studio ResNet database ready for data analysis. MedScan is more than a web search engine. Indeed, the output of a Google search can be channeled into MedScan for example. Web searches, like Google, are excellent at finding items as a result of a query. A quick look at the output list usually locates the item for which you are looking. This approach however, is not well suited for information and knowledge gathering. Also, once information is gathered, where do you put it for later computational use? MedScan meets this challenge for the area of biomedical literature and biomedical online information. PubMed meets the needs for a central repository of biomedical literature. Researchers can go to PubMed and search for any topic and articles of interest, much like a web type of search. However, just like a web type of search, PubMed also provides a list of all the hits with a link to the articles. If a single article, or even just a few, are sought, this search approach is useful. Alternatively, MedScan will list all the articles of interest but additionally scans the text for relationships, highlights these relationships in the articles and then lists these relationships and the biological molecules and processes involved in the relationships in separate tables. The tables of relationships can be viewed graphically in Pathway Studio and can be saved into the ResNet database for use in experimental data analysis.

Proper citation: MedScan (RRID:SCR_003314) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/dranew/defuse

Software package for gene fusion discovery using RNA-Seq data. It uses clusters of discordant paired end alignments to inform a split read alignment analysis for finding fusion boundaries.

Proper citation: deFuse (RRID:SCR_003279) Copy   

•   Source: SciCrunch Registry

http://rostlab.org/services/nlsdb/

A database of nuclear localization signals (NLSs) and of nuclear proteins targeted to the nucleus by NLS motifs. NLSs are short stretches of residues mediating transport of nuclear proteins into the nucleus. The database contains 114 experimentally determined NLSs that were obtained through an extensive literature search. Using "in silico mutagenesis" this set was extended to 308 experimental and potential NLSs. This final set matched over 43% of all known nuclear proteins and matches no currently known non-nuclear protein. NLSdb contains over 6000 predicted nuclear proteins and their targeting signals from the PDB and SWISS-PROT/TrEMBL databases. The database also contains over 12 500 predicted nuclear proteins from six entirely sequenced eukaryotic proteomes (Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana and Saccharomyces cerevisiae). NLS motifs often co-localize with DNA-binding regions. This observation was used to also annotate over 1500 DNA-binding proteins. From this site you can: * Query NLSdb * Find out how to use NLSdb * Browse the entries in NLSdb * Find out if your protein has an NLS using PredictNLS * Predict subcellular localization of your protein using LOCtree

Proper citation: NLSdb: a database of nuclear localization signals (RRID:SCR_003273) Copy   

•   Source: SciCrunch Registry

http://abi.inf.uni-tuebingen.de/Services/MultiLoc2

An extensive high-performance subcellular protein localization prediction system that incorporates phylogenetic profiles and Gene Ontology terms to yield higher accuracies compared to its previous version. Moreover, it outperforms other prediction systems in two benchmarks studies. A downloadable version of MultiLoc2 for local use is also available.

Proper citation: MultiLoc (RRID:SCR_003151) Copy   

•   Source: SciCrunch Registry

http://www.jax.org/cyto/index.html

Maintains and distributes chromosome aberration stocks that provide primarily mouse models for Down syndrome. The Resource currently provides models for Down syndrome research, including: Rb(6.16)24Lub x Rb(16.17)7Bnr F1 hybrids that are used to produce Chr 16 trisomy (Ts16) embryos, which have many of the fetal developmental features of DS, and; Ts(1716)65Dn, segmental trisomy mice that survive to adulthood and have many of the features of DS. The Resource also includes stocks with selected reciprocal translocations involving Chr 16 and some Chr 16 transgenic stocks. In addition, a large number of Robertsonian chromosome stocks are held as frozen embryos in the Cryopreservation Resource. Each mouse chromosome is present in at least two different Robertsonian chromosomes in these strains so that specific trisomies for each of the 19 mouse autosomes can be produced. Breeding pairs and individual mice are provided.

Proper citation: Jackson Laboratory Cytogenetic Models Resource (RRID:SCR_003270) Copy   

•   Source: SciCrunch Registry

http://braininfo.rprc.washington.edu

Portal to neuroanatomical information on the Web that helps you identify structures in the brain and provides a variety of information about each structure by porting you to the best of 1500 web pages at 100 other neuroscience sites. BrainInfo consists of three basic components: NeuroNames, a developing database of definitions of neuroanatomic structures in four species, their most common acronyms and their names in eight languages; NeuroMaps, a digital atlas system based on 3-D canonical stereotaxic atlases of rhesus macaque and mouse brains and programs that enable one to map data to standard surface and cross-sectional views of the brains for presentation and publication; and the NeuroMaps precursor: Template Atlas of the Primate Brain, a 2-D stereotaxic atlas of the longtailed (fascicularis) macaque brain that shows the locations of some 250 architectonic areas of macaque cortex. The NeuroMaps atlases will soon include a number of overlays showing the locations of cortical areas and other neuroscientific data in the standard frameworks of the macaque and mouse atlases. Viewers are encouraged to use NeuroNames as a stable source of unique standard terms and acronyms for brain structures in publications, illustrations and indexing systems; to use templates extracted from the NeuroMaps macaque and mouse brain atlases for presenting neuroscientific information in image format; and to use the Template Atlas for warping to MRIs or PET scans of the macaque brain to estimate the stereotaxic locations of structures.

Proper citation: BrainInfo (RRID:SCR_003142) Copy   

•   Source: SciCrunch Registry

http://csbio.unc.edu/genescissors/

Software for detecting and correcting spurious transcriptome inference due to RNAseq reads misalignment.

Proper citation: GeneScissors (RRID:SCR_003146) Copy   

•   Source: SciCrunch Registry

http://primer3.ut.ee

Tool used to design PCR primers from DNA sequence - often in high-throughput genomics applications. It does everything from mispriming libraries to sequence quality data to the generation of internal oligos.

Proper citation: Primer3 (RRID:SCR_003139) Copy   

•   Source: SciCrunch Registry

http://protege.stanford.edu

Protege is a free, open-source platform that provides a growing user community with a suite of tools to construct domain models and knowledge-based applications with ontologies. At its core, Protege implements a rich set of knowledge-modeling structures and actions that support the creation, visualization, and manipulation of ontologies in various representation formats. Protege can be customized to provide domain-friendly support for creating knowledge models and entering data. Further, Protege can be extended by way of a plug-in architecture and a Java-based Application Programming Interface (API) for building knowledge-based tools and applications. An ontology describes the concepts and relationships that are important in a particular domain, providing a vocabulary for that domain as well as a computerized specification of the meaning of terms used in the vocabulary. Ontologies range from taxonomies and classifications, database schemas, to fully axiomatized theories. In recent years, ontologies have been adopted in many business and scientific communities as a way to share, reuse and process domain knowledge. Ontologies are now central to many applications such as scientific knowledge portals, information management and integration systems, electronic commerce, and semantic web services. The Protege platform supports two main ways of modeling ontologies: * The Protege-Frames editor enables users to build and populate ontologies that are frame-based, in accordance with the Open Knowledge Base Connectivity protocol (OKBC). In this model, an ontology consists of a set of classes organized in a subsumption hierarchy to represent a domain's salient concepts, a set of slots associated to classes to describe their properties and relationships, and a set of instances of those classes - individual exemplars of the concepts that hold specific values for their properties. * The Protege-OWL editor enables users to build ontologies for the Semantic Web, in particular in the W3C's Web Ontology Language (OWL). An OWL ontology may include descriptions of classes, properties and their instances. Given such an ontology, the OWL formal semantics specifies how to derive its logical consequences, i.e. facts not literally present in the ontology, but entailed by the semantics. These entailments may be based on a single document or multiple distributed documents that have been combined using defined OWL mechanisms (see the OWL Web Ontology Language Guide). Protege is based on Java, is extensible, and provides a plug-and-play environment that makes it a flexible base for rapid prototyping and application development.

Proper citation: Protege (RRID:SCR_003299) Copy   

•   Source: SciCrunch Registry

http://phenome.jax.org/

Database enables integration of genomic and phenomic data by providing access to primary experimental data, data collection protocols and analysis tools. Data represent behavioral, morphological and physiological disease-related characteristics in naive mice and those exposed to drugs, environmental agents or other treatments. Collaborative standardized collection of measured data on laboratory mouse strains to characterize them in order to facilitate translational discoveries and to assist in selection of strains for experimental studies. Includes baseline phenotype data sets as well as studies of drug, diet, disease and aging effect., protocols, projects and publications, and SNP, variation and gene expression studies. Provides tools for online analysis. Data sets are voluntarily contributed by researchers from variety of institutions and settings, or retrieved by MPD staff from open public sources. MPD has three major types of strain-centric data sets: phenotype strain surveys, SNP and variation data, and gene expression strain surveys. MPD collects data on classical inbred strains as well as any fixed-genotype strains and derivatives that are openly acquirable by the research community. New panels include Collaborative Cross (CC) lines and Diversity Outbred (DO) populations. Phenotype data include measurements of behavior, hematology, bone mineral density, cholesterol levels, endocrine function, aging processes, addiction, neurosensory functions, and other biomedically relevant areas. Genotype data are primarily in the form of single-nucleotide polymorphisms (SNPs). MPD curates data into a common framework by standardizing mouse strain nomenclature, standardizing units (SI where feasible), evaluating data (completeness, statistical power, quality), categorizing phenotype data and linking to ontologies, conforming to internal style guides for titles, tags, and descriptions, and creating comprehensive protocol documentation including environmental parameters of the test animals. These elements are critical for experimental reproducibility.

Proper citation: Mouse Phenome Database (MPD) (RRID:SCR_003212) Copy   

•   Source: SciCrunch Registry

http://www.emdataresource.org/

Portal for deposition and retrieval of cryo electron microscopy (3DEM) density maps, atomic models, and associated metadata. Global resource for 3 Dimensional Electron Microscopy structure data archiving and retrieval, news, events, software tools, data standards, validation methods.

Proper citation: EMDataResource.org (RRID:SCR_003207) Copy   

•   Source: SciCrunch Registry

http://dip.doe-mbi.ucla.edu/

Database to catalog experimentally determined interactions between proteins combining information from a variety of sources to create a single, consistent set of protein-protein interactions that can be downloaded in a variety of formats. The data were curated, both, manually and also automatically using computational approaches that utilize the the knowledge about the protein-protein interaction networks extracted from the most reliable, core subset of the DIP data. Because the reliability of experimental evidence varies widely, methods of quality assessment have been developed and utilized to identify the most reliable subset of the interactions. This CORE set can be used as a reference when evaluating the reliability of high-throughput protein-protein interaction data sets, for development of prediction methods, as well as in the studies of the properties of protein interaction networks. Tools are available to analyze, visualize and integrate user's own experimental data with the information about protein-protein interactions available in the DIP database. The DIP database lists protein pairs that are known to interact with each other. By interact they mean that two amino acid chains were experimentally identified to bind to each other. The database lists such pairs to aid those studying a particular protein-protein interaction but also those investigating entire regulatory and signaling pathways as well as those studying the organization and complexity of the protein interaction network at the cellular level. Registration is required to gain access to most of the DIP features. Registration is free to the members of the academic community. Trial accounts for the commercial users are also available.

Proper citation: Database of Interacting Proteins (DIP) (RRID:SCR_003167) Copy   

•   Source: SciCrunch Registry

http://www.sysbio.se/piano/

Software R-package for running gene set analysis using various statistical methods, from different gene level statistics and a wide range of gene-set collections. The Piano package contains functions for combining the results of multiple runs of gene set analyses.

Proper citation: Piano (RRID:SCR_003200) Copy   

•   Source: SciCrunch Registry

http://cmb.molgen.mpg.de/2ndGenerationSequencing/Solas/

Software package for the statistical language R, devoted to the analysis of next generation short read data of RNA-seq transcripts. It provides predictions of alternative exons in a single condition/cell sample, predictions of differential alternative exons between two conditions/cell samples, and quantification of alternative splice forms in a single condition/cell sample.

Proper citation: Solas (RRID:SCR_003168) Copy   

•   Source: SciCrunch Registry