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http://eurofung.net/index.php?option=com_content&task=section&id=3&Itemid=4

The Eurofung project is a Coordination Action with the aim of developing a strategy to build up and maintain an integrated, sustainable European genomic database required for innovative genomics research of filamentous fungal model organisms of interest. This database will become a crystallization point for related systems and then could be integrated and conserved in a central European genomic database. The consortium counts 32 member laboratories, three of which have partner status. A Fungal Industrial Platform (FIP) of 13 members is also associated with the project. The project focuses on several filamentous fungi for different reasons. Aspergillus nidulans has a long record of use as a fungal model organism. Aspergillus niger, Trichoderma reesei and Penicillium chrysogenum are important cell factories used for the production of enzymes and metabolites including compounds such as Beta-lactams with benefits to human health. The human pathogen Aspergillus fumigatus serves not only as a model pathogen, but becomes more and more a serious threat to human health. The project contributes to create the conditions and facilities within Europe to widely apply all genomics technologies in filamentous fungal research. This will greatly expand our knowledge about filamentous fungi. This new genomics information will thus be beneficial to European biotechnology industries and help to improve the prevention and treatment of fungal disease. Expected results: The main results expected from this project are: - The contribution of the community to the manual annotation of important fungal genomes through annotation jamborees. - The realization of an integrated sustainable fungal genomic database through collaboration with bioinformatics centers and incorporation of the community data. - The realization of a fungal genomics knowledge base for the Eurofungbase community and the European fungal biotech industry through meetings, workshops and web-based information. - Intensified collaboration between the members of the network including the participating industries, thus strengthening the infrastructure for high quality fungal genomics research in Europe and furthermore determining joint research targets for the future. -Individualized training of a next generation of young scientists in fungal genomics and biotechnological research.

Proper citation: Eurofungbase (RRID:SCR_007094) Copy   

•   Source: SciCrunch Registry

http://www.semantic-mediawiki.org/wiki/Semantic_MediaWiki

A free, open-source extension to MediaWiki - the wiki software that powers Wikipedia - that helps to search, organize, tag, browse, evaluate, and share the wiki''s content. While traditional wikis contain only text which computers can neither understand nor evaluate, SMW adds semantic annotations that allow a wiki to function as a collaborative database. Semantic MediaWiki introduces some additional markup into the wiki-text which allows users to add semantic annotations to the wiki. While this first appears to make things more complex, it can also greatly simplify the structure of the wiki, help users to find more information in less time, and improve the overall quality and consistency of the wiki. A large number of related extensions have been created that extend the ability to edit, display and browse through the data stored by SMW: the term Semantic MediaWiki is sometimes used to refer to this entire family of extensions.

Proper citation: Semantic MediaWiki (RRID:SCR_006246) Copy   

•   Source: SciCrunch Registry

http://www.wf4ever-project.org/

Project to addresses challenges associated with the preservation of scientific experiments in data-intensive science, including: * The definition of models to describe, in a standard way, scientific experiments by means of workflow-centric Research Objects, which comprise scientific workflows, the provenance of their executions, interconnections between workflows and related resources (e.g., datasets, publications, etc.), and social aspects related to such scientific experiments. * The collection of best practices for the creation and management of Research Objects. * The analysis and management of decay in scientific workflows. To address these challenges they are creating an architecture and tooling for the access, manipulation, sharing, reuse and evolution of Research Objects in a range of disciplines. This will result into the next generation RO-enabled myExperiment.

Proper citation: Workflow4Ever (RRID:SCR_005939) Copy   

•   Source: SciCrunch Registry

http://xldb.fc.ul.pt/biotools/rebil/goa/

A tool for assisting the GO annotation of UniProt entries by linking the GO terms present in the uncurated annotations with evidence text automatically extracted from the documents linked to UniProt entries. Platform: Online tool

Proper citation: GoAnnotator (RRID:SCR_005792) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/orienTM/

A computer software that utilizes an initial definition of transmembrane segments to predict the topology of transmembrane proteins from their sequence. It uses position-specific statistical information for amino acid residues which belong to putative non-transmembrane segments derived from a statistical analysis of non-transmembrane regions of membrane proteins stored in the SwissProt database. Its accuracy compares well with that of other popular existing methods.

Proper citation: orienTM (RRID:SCR_006218) Copy   

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http://athina.biol.uoa.gr/PRED-TMR2/

A web server that classifies proteins into two classes from their sequences alone: the membrane protein class and the non-membrane protein class. This may be important in the functional assignment and analysis of open reading frames (ORF''s) identified in complete genomes and, especially, those ORF''s that correspond to proteins with unknown function. The network has a simple hierarchical feed-forward topology and a limited number of neurons which makes it very fast. By using only information contained in 11 protein sequences, the method was able to identify, with 100% accuracy, all membrane proteins with reliable topologies collected from several papers in the literature. Applied to a test set of 995 globular, water-soluble proteins, the neural network classified falsely 23 of them in the membrane protein class (97.7% of correct assignment). The method was also applied to the complete SWISS-PROT database with considerable success and on ORF''s of several complete genomes. The neural network developed was associated with the PRED-TMR algorithm (Pasquier,C., Promponas,V.J., Palaios,G.A., Hamodrakas,J.S. and Hamodrakas,S.J., 1999) in a new application package called PRED-TMR2.

Proper citation: PRED-TMR2 (RRID:SCR_006205) Copy   

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http://athina.biol.uoa.gr/PRED-TMR/

A web server that predicts transmembrane domains in proteins using solely information contained in the sequence itself. The algorithm refines a standard hydrophobicity analysis with a detection of potential termini (edges, starts and ends) of transmembrane regions. This allows both to discard highly hydrophobic regions not delimited by clear start and end configurations and to confirm putative transmembrane segments not distinguishable by their hydrophobic composition. The accuracy obtained on a test set of 101 non homologous transmembranes proteins with reliable topologies compares well with that of other popular existing methods. Only a slight decrease in prediction accuracy was observed when the algorithm was applied to all transmembrane proteins of the SwissProt database (release 35).

Proper citation: PRED-TMR (RRID:SCR_006203) Copy   

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http://www.gene-regulation.com/pub/databases.html#transpath

Database on eukaryotic transcription factors, their experimentally-proven binding sites, consensus binding sequences (positional weight matrices) and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. It can either be used as an encyclopedia, for both specific and general information on signal transduction, or can serve as a network analyzer. Cross-references to important sequence and signature databases such as EMBL/GenBank UniProt/Swiss-Prot InterPro or Ensembl EntrezGene RefSeq are provided. The database is equipped with the tools for data visualization and analysis. It has three modules: the first one is the data, which have been manually extracted, mostly from the primary literature; the second is PathwayBuilder, which provides several different types of network visualization and hence facilitates understanding; the third is ArrayAnalyzer, which is particularly suited to gene expression array interpretation, and is able to identify key molecules within signalling networks (potential drug targets). These key molecules could be responsible for the coordinated regulation of downstream events. Manual data extraction focuses on direct reactions between signalling molecules and the experimental evidence for them, including species of genes/proteins used in individual experiments, experimental systems, materials and methods. This combination of materials and methods is used in TRANSPATH to assign a quality value to each experimentally proven reaction, which reflects the probability that this reaction would happen under physiological conditions. Another important feature in TRANSPATH is the inclusion of transcription factor-gene relations, which are transferred from TRANSFAC, a database focused on transcription regulation and transcription factors. Since interactions between molecules are mainly direct, this allows a complete and stepwise pathway reconstruction from ligands to regulated genes.

Proper citation: TRANSPATH (RRID:SCR_005640) Copy   

•   Source: SciCrunch Registry

http://www.gotaxexplorer.de/

GOTaxExplorer presents a new approach to comparative genomics that integrates functional information and families with the taxonomic classification. It integrates UniProt, Gene Ontology, NCBI Taxonomy, Pfam and SMART in one database. GOTaxExplorer provides four different query types: selection of entity sets, comparison of sets of Pfam families, semantic comparison of sets of GO terms, functional comparison of sets of gene products. This permits to select custom sets of GO terms, families or taxonomic groups. For example, it is possible to compare arbitrarily selected organisms or groups of organisms from the taxonomic tree on the basis of the functionality of their genes. Furthermore, it enables to determine the distribution of specific molecular functions or protein families in the taxonomy. The comparison of sets of GO terms allows to assess the semantic similarity of two different GO terms. The functional comparison of gene products makes it possible to identify functionally equivalent and functionally related gene products from two organisms on the basis of GO annotations and a semantic similarity measure for GO. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOTaxExplorer (RRID:SCR_005720) Copy   

•   Source: SciCrunch Registry

http://vibez.informatik.uni-freiburg.de/

An imaging and image analysis framework for virtual colocalization studies in larval zebrafish brains, currently available for 72hpf, 48hpf and 96hpf old larvae. ViBE-Z contains a database with precisely aligned gene expression patterns (1����m^3 resolution), an anatomical atlas, and a software. This software creates high-quality data sets by fusing multiple confocal microscopic image stacks, and aligns these data sets to the standard larva. The ViBE-Z database and atlas are stored in HDF5 file format. They are freely available for download. ViBE-Z provides a software that automatically maps gene expression data with cellular resolution to a 3D standard larval zebrafish (Danio rerio) brain. ViBE-Z enhances the data quality through fusion and attenuation correction of multiple confocal microscope stacks per specimen and uses a fluorescent stain of cell nuclei for image registration. It automatically detects 14 predefined anatomical landmarks for aligning new data with the reference brain. ViBE-Z performs colocalization analysis in expression databases for anatomical domains or subdomains defined by any specific pattern. The ViBE-Z database, atlas and software are provided via a web interface.

Proper citation: ViBE-Z (RRID:SCR_005895) Copy   

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http://www.ebi.ac.uk/Tools/pfa/iprscan/

Software package for functional analysis of sequences by classifying them into families and predicting presence of domains and sites. Scans sequences against InterPro's signatures. Characterizes nucleotide or protein function by matching it with models from several different databases. Used in large scale analysis of whole proteomes, genomes and metagenomes. Available as Web based version and standalone Perl version and SOAP Web Service.

Proper citation: InterProScan (RRID:SCR_005829) Copy   

•   Source: SciCrunch Registry

http://www.livinghuman.org/

Distributed repository of anatomo-functional data and of simulation algorithms, fully integrated into a seamless simulation environment and directly accessible. This infrastructure will be used to create the physiome of the human musculo-skeletal system.

Proper citation: LHP LHDL (RRID:SCR_005928) Copy   

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http://www.vectorbase.org

Bioinformatics Resource Center for invertebrate vectors. Provides web-based resources to scientific community conducting basic and applied research on organisms considered potential agents of biowarfare or bioterrorism or causing emerging or re-emerging diseases.

Proper citation: VectorBase (RRID:SCR_005917) Copy   

•   Source: SciCrunch Registry

https://www.infrafrontier.eu/emma/

Non-profit repository for the collection, archiving (via cryopreservation) and distribution of relevant mutant strains essential for basic biomedical research. Users may browse by strain, gene, phenotype, or human disease. Its primary objective is to establish and manage a unified repository for maintaining medically relevant mouse mutants and making them available to the scientific community. Therefore, EMMA archives mutant strains and distributes them to requesting researchers. EMMA also hosts courses in cryopreservation, to promote the use and dissemination of frozen embryos and spermatozoa. Dissemination of knowledge is further fostered by a dedicated resource database. Anybody who wants their mutant mouse strains cryopreserved may deposit strains with EMMA. However depositors must be aware that these strains become freely available to other researchers after being deposited.With more than 8400 mutant mouse strains and asmall but increasing number of rat mutant strains available, EMMA is the primary mouse repository in Europe and the third largest non-profit repository worldwide.

Proper citation: European Mouse Mutant Archive (RRID:SCR_006136) Copy   

•   Source: SciCrunch Registry

https://protein.mpiib-berlin.mpg.de/cgi-bin/pdbs/2d-page/extern/index.cgi

The Proteome 2D-PAGE Database system for microbial research is a curated database for storing and investigating proteomics data. Software tools are available and for data submission, please contact the Database Curator. Established at the Max Plank Institution for Infection Biology, this system contains four interconnected databases: i.) 2D-PAGE Database: Two dimensional electrophoresis (2-DE) and mass spectrometry of diverse microorganisms and other organisms. This database currently contains 4971 identified spots and 1228 mass peaklists in 44 reference maps representing experiments from 24 different organisms and strains. The data were submitted by 84 Submitters from 24 Institutes and 12 nations. It also contains various software tools that are important in formatting and analyzing gels and mass peaks; software include: *TopSpot: Scanning the gel, editing the spots and saving the information *Fragmentation: Fragmentation of the gel image into sections *MS-Screener: Perl script to compare the similarity of MALDI-PMF peaklists *MS-Screener update: MS-Screener can be used to compare mass spectra (MALDI-MS(/MS) as well as ESI-MS/MS spectra) on the basis of their peak lists (.dta, .pkm, .pkt, or .txt files), to recalibrate mass spectra, to determine and eliminate exogenous contaminant peaks, and to create matrices for cluster analyses. *GelCali: Online calibration of the Mr- and pI-axis of 2-DE gels with mathematical regression methods ii.)Isotope Coded Affinity Tag (ICAT)-LC/MS database: Isotope Coded Affinity Tag (ICAT)-LC/MS data for Mycobacterium tuberculosis strain BCG versus H37Rv. iii.) FUNC_CLASS database: Functional classification of diverse microorganism. This database also integrates genomic, proteomic, and metabolic data. iv.) DIFF database: Presentation of differently regulated proteins obtained by comparative proteomic experiments using computerized gel image analysis.

Proper citation: Proteome 2D-PAGE Database (RRID:SCR_001678) Copy   

•   Source: SciCrunch Registry

http://videolectures.net/

Award-winning free and open access educational video lectures repository. The lectures are given by distinguished scholars and scientists at the most important and prominent events like conferences, summer schools, workshops and science promotional events from many fields of Science. The portal is aimed at promoting science, exchanging ideas and fostering knowledge sharing by providing high quality didactic contents not only to the scientific community but also to the general public. All lectures, accompanying documents, information and links are systematically selected and classified through the editorial process taking into account also users' comments.

Proper citation: VideoLectures.NET (RRID:SCR_001972) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/genre/proj/yeast/index.jsp

The MIPS Comprehensive Yeast Genome Database (CYGD) aims to present information on the molecular structure and functional network of the entirely sequenced, well-studied model eukaryote, the budding yeast Saccharomyces cerevisiae. In addition, the data of various projects on related yeasts are used for comparative analysis.

Proper citation: CYGD - Comprehensive Yeast Genome Database (RRID:SCR_002289) Copy   

•   Source: SciCrunch Registry

http://www.mged.org/Workgroups/MAGE/mage-ml.html

A language / data exchange format designed to describe and communicate information about microarray based experiments that is based on XML and can describe microarray designs, microarray manufacturing information, microarray experiment setup and execution information, gene expression data and data analysis results. MAGE-ML has been automatically derived from Microarray Gene Expression Object Model (MAGE-OM), which is developed and described using the Unified Modelling Language (UML) -- a standard language for describing object models. Descriptions using UML have an advantage over direct XML document type definitions (DTDs), in many respects. First they use graphical representation depicting the relationships between different entities in a way which is much easier to follow than DTDs. Second, the UML diagrams are primarily meant for humans, while DTDs are meant for computers. Therefore MAGE-OM should be considered as the primary model, and MAGE-ML will be explained by providing simplified fragments of MAGE-OM, rather then XML DTD or XML Schema. (from the description by Ugis Sarkans) The field of gene expression experiments has several distinct technologies that a standard must include. These include single vs. dual channel experiments, cDNA vs. oligonucleotides. Because of these different technologies and different types of gene expression experiments, it is not expected that all aspects of the standard will be used by all organizations. Given the massive amount of data associated with a single set of experiments, it is felt that Extensible Markup Language (XML) is the best way to describe the data. The use of a Document Type Definition (DTD) allows a well-defined tag set, a vocabulary, to describe the domain of gene expression experiments. It also has the virtue of compressing very well so that files in an XML format compress to ten percent of their original size. XML is now widely accepted as a data exchange format across multiple platforms.

Proper citation: MicroArray and Gene Expression Markup Language (RRID:SCR_003023) Copy   

•   Source: SciCrunch Registry

http://briansimulator.org/

Software Python package for simulating spiking neural networks. Useful for neuroscientific modelling at systems level, and for teaching computational neuroscience. Intuitive and efficient neural simulator.

Proper citation: Brian Simulator (RRID:SCR_002998) Copy   

•   Source: SciCrunch Registry

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