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http://www.fruitfly.org

Database on the sequence of the euchromatic genome of Drosophila melanogaster In addition to genomic sequencing, the BDGP is 1) producing gene disruptions using P element-mediated mutagenesis on a scale unprecedented in metazoans; 2) characterizing the sequence and expression of cDNAs; and 3) developing informatics tools that support the experimental process, identify features of DNA sequence, and allow us to present up-to-date information about the annotated sequence to the research community. Resources * Universal Proteomics Resource: Search for clones for expression and tissue culture * Materials: Request genomic or cDNA clones, library filters or fly stocks * Download Sequence data sets and annotations in fasta or xml format by http or ftp * Publications: Browse or download BDGP papers * Methods: BDGP laboratory protocols and vector maps * Analysis Tools: Search sequences for CRMs, promoters, splice sites, and gene predictions * Apollo: Genome annotation viewer and editor September 15, 2009 Illumina RNA-Seq data from 30 developmental time points of D. melanogaster has been submitted to the Short Read Archive at NCBI as part of the modENCODE project. The data set currently contains 2.2 billion single-end and paired reads and over 201 billion base pairs.

Proper citation: Berkeley Drosophila Genome Project (RRID:SCR_013094) Copy   

•   Source: SciCrunch Registry

http://www.rdkit.org/

An open-source cheminformatics and machine-learning toolkit that is useable from Java or Python. It includes a collection of standard cheminformatics functionality for molecule I/O, substructure searching, chemical reactions, coordinate generation (2D or 3D), fingerprinting, etc., as well as a high-performance database cartridge for working with molecules using the PostgreSQL database. Documentation is available on the main website.

Proper citation: RDKit: Open-Source Cheminformatics Software (RRID:SCR_014274) Copy   

•   Source: SciCrunch Registry

http://prospector.ucsf.edu

A package of over twenty mass spectrometry-based tools primarily geared toward proteomic data analysis and database mining. It can be run from the command line, but is primarily used through a web browser, and there is a public website that allows anyone to use the software without local installation. Tandem mass spectrometry analysis tools are used for database searching and identification of peptides, including post-translationally modified peptides and cross-linked peptides. Support for isotope and label-free quantification from this type of data is provided. MS-Viewer software allows sharing and displaying of annotated spectra from many different tandem mass spectrometry data analysis packages. Other tools include software for analyzing peptide mass fingerprinting data (MS-Fit); prediction of theoretical fragmentation of peptides (MS-Product); theoretical chemical or enzymatic digestion of proteins (MS-Digest); and theoretical modeling of the isotope distribution of any chemical, including peptides (MS-Isotope). Searches using amino acid sequence can be used to identify homologous peptides in a database (MS-Pattern); the use of the combination of amino acid sequence and masses can be used for homologous peptide and protein identification using MS-Homology. Tandem mass spectrometry peak list files can be filtered for the presence of certain peaks or neutral losses using MS-Filter. Given a list of proteins, MS-Bridge can report all potential cross-linked peptide combinations of a specified mass. Given a precursor peptide mass and information about known amino acid presence, absence, or modifications, MS-Comp can report all amino acid combinations that could lead to the observed mass.

Proper citation: Protein Prospector (RRID:SCR_014558) Copy   

•   Source: SciCrunch Registry

https://www.molinspiration.com/

Broad range of cheminformatics software tools supporting molecule manipulation and processing, including SMILES and SDfile conversion, normalization of molecules, generation of tautomers, molecule fragmentation, calculation of various molecular properties needed in QSAR, molecular modelling and drug design, high quality molecule depiction, molecular database tools supporting substructure and similarity searches. Molinspiration tools are platform independent and may be run on any PC, Mac, UNIX or LINUX machine. Software is distributed in form of engines, which may be used as stand-alone computational engines, used to power web-based tools, or incorporated into larger in-house Java applications.

Proper citation: Molinspiration (RRID:SCR_018525) Copy   

•   Source: SciCrunch Registry

https://www.ngvbcc.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. Archiving services, insertional site analysis, pharmacology and toxicology resources, and reagent repository for academic investigators and others conducting gene therapy research. Databases and educational resources are open to everyone. Other services are limited to gene therapy investigators working in academic or other non-profit organizations. Stores reserve or back-up clinical grade vector and master cell banks. Maintains samples from any gene therapy related Pharmacology or Toxicology study that has been submitted to FDA by U.S. academic investigator that require storage under Good Laboratory Practices. For certain gene therapy clinical trials, FDA has required post-trial monitoring of patients, evaluating clinical samples for evidence of clonal expansion of cells. To help academic investigators comply with this FDA recommendation, the NGVB offers assistance with clonal analysis using LAM-PCR and LM-PCR technology.

Proper citation: National Gene Vector Biorepository (RRID:SCR_004760) Copy   

•   Source: SciCrunch Registry

http://www.atsdr.cdc.gov/toxprofiles

A database of information about contaminants found at hazardous waste sites. The toxicological profiles are cataloged by chemical with the NTIS order number.

Proper citation: CDC Toxprofiles (RRID:SCR_000900) Copy   

•   Source: SciCrunch Registry

http://img.jgi.doe.gov/cgi-bin/m/main.cgi

Resource for analysis and annotation of genome and metagenome datasets in comprehensive comparative context. IMG provides users with tools for analyzing publicly available genome datasets and metagenome datasets.

Proper citation: IMG System (RRID:SCR_002965) Copy   

•   Source: SciCrunch Registry

http://soybase.org

Professionally curated repository for genetics, genomics and related data resources for soybean that contains the most current genetic, physical and genomic sequence maps integrated with qualitative and quantitative traits. SoyBase includes annotated Williams 82 genomic sequence and associated data mining tools. The genetic and sequence views of the soybean chromosomes and the extensive data on traits and phenotypes are extensively interlinked. This allows entry to the database using almost any kind of available information, such as genetic map symbols, soybean gene names or phenotypic traits. The repository maintains controlled vocabularies for soybean growth, development, and traits that are linked to more general plant ontologies. Contributions to SoyBase or the Breeder''s Toolbox are welcome.

Proper citation: SoyBase (RRID:SCR_005096) Copy   

•   Source: SciCrunch Registry

http://www.chem.qmul.ac.uk/iubmb/enzyme/

Recommendations of the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology on the nomenclature and classification of enzymes by the reactions they catalyze. Also included are links to individual documents and advice is provided on how to suggest new enzymes for listing, or correction of existing entries. The common names of all listed enzymes are listed, along with their EC numbers. Where an enzyme has been deleted or transferred to another EC number, this information is also indicated. Each list is linked to either separate entries for each entry or to files with up to 50 enzymes in each file. A start has been made in showing the pathways in which enzymes participate. For other enzymes a glossary entry has been added which may be just a systematic name or a link to a graphic representation. The glossary from Enzyme Nomenclature, 1992 may also be consulted. This has been updated with subsequent glossary entries. Each enzyme entry has links to other databases. Enzyme Subclasses provide links to a list of sub-subclasses which in turn list the enzymes linked to separate files for each enzyme, or to a list as part of a file with up to 50 enzymes per file.

Proper citation: Enzyme Nomenclature (RRID:SCR_006583) Copy   

•   Source: SciCrunch Registry

http://snpeffect.vib.be/

A database for phenotyping human single nucleotide polymorphisms (SNPs)that primarily focuses on the molecular characterization and annotation of disease and polymorphism variants in the human proteome. They provide a detailed variant analysis using their tools such as: * TANGO to predict aggregation prone regions * WALTZ to predict amylogenic regions * LIMBO to predict hsp70 chaperone binding sites * FoldX to analyse the effect on structure stability Further, SNPeffect holds per-variant annotations on functional sites, structural features and post-translational modification. The meta-analysis tool enables scientists to carry out a large scale mining of SNPeffect data and visualize the results in a graph. It is now possible to submit custom single protein variants for a detailed phenotypic analysis., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SNPeffect (RRID:SCR_005091) Copy   

•   Source: SciCrunch Registry

http://smd.stanford.edu/cgi-bin/source/sourceSearch

SOURCE compiles information from several publicly accessible databases, including UniGene, dbEST, UniProt Knowledgebase, GeneMap99, RHdb, GeneCards and LocusLink. GO terms associated with LocusLink entries appear in SOURCE. The mission of SOURCE is to provide a unique scientific resource that pools publicly available data commonly sought after for any clone, GenBank accession number, or gene. SOURCE is specifically designed to facilitate the analysis of large sets of data that biologists can now produce using genome-scale experimental approaches Platform: Online tool

Proper citation: SOURCE (RRID:SCR_005799) Copy   

•   Source: SciCrunch Registry

http://cmr.jcvi.org/tigr-scripts/CMR/CmrHomePage.cgi

Database of all of the publicly available, complete prokaryotic genomes. In addition to having all of the organisms on a single website, common data types across all genomes in the CMR make searches more meaningful, and cross genome analysis highlight differences and similarities between the genomes. CMR offers a wide variety of tools and resources, all of which are available off of our menu bar at the top of each page. Below is an explanation and link for each of these menu options. * Genome Tools: Find organism lists as well as summary information and analyses for selected genomes. * Searches: Search CMR for genes, genomes, sequence regions, and evidence. * Comparative Tools: Compare multiple genomes based on a variety of criteria, including sequence homology and gene attributes. SNP data is also found under this menu. * Lists: Select and download gene, evidence, and genomic element lists. * Downloads: Download gene sequences or attributes for CMR organisms, or go to our FTP site. * Carts: Select genome preferences from our Genome Cart or download your Gene Cart genes. The Omniome is the relational database underlying the CMR and it holds all of the annotation for each of the CMR genomes, including DNA sequences, proteins, RNA genes and many other types of features. Associated with each of these DNA features in the Omniome are the feature coordinates, nucleotide and protein sequences (where appropriate), and the DNA molecule and organism with which the feature is associated. Also available are evidence types associated with annotation such as HMMs, BLAST, InterPro, COG, and Prosite, as well as individual gene attributes. In addition, the database stores identifiers from other centers such as GenBank and SwissProt, as well as manually curated information on each genome or each DNA molecule including website links. Also stored in the Omniome are precomputed homology data, called All vs All searches, used throughout the CMR for comparative analysis.

Proper citation: JCVI CMR (RRID:SCR_005398) Copy   

•   Source: SciCrunch Registry

http://treebase.org/treebase-web/

Repository of phylogenetic information, specifically user-submitted phylogenetic trees and the data used to generate them. TreeBASE accepts all kinds of phylogenetic data (e.g., trees of species, trees of populations, trees of genes) representing all biotic taxa. Data in TreeBASE are exposed to the public if they are used in a publication that is in press or published in a peer-reviewed scientific journal, book, conference proceedings, or thesis. Data used in publications that are in preparation or in review can be submitted to TreeBASE but will not be available to the public until they have passed peer review.

Proper citation: TreeBASE (RRID:SCR_005688) Copy   

•   Source: SciCrunch Registry

http://www.gbif.org/

The Global Biodiversity Information Facility (GBIF) was established by governments in 2001 to encourage free and open access to biodiversity data, via the Internet. Through a global network of countries and organizations, GBIF promotes and facilitates the mobilization, access, discovery and use of information about the occurrence of organisms over time and across the planet. GBIF provides three core services and products: # An information infrastructure an Internet-based index of a globally distributed network of interoperable databases that contain primary biodiversity data information on museum specimens, field observations of plants and animals in nature, and results from experiments so that data holders across the world can access and share them # Community-developed tools, standards and protocols the tools data providers need to format and share their data # Capacity-building the training, access to international experts and mentoring programs that national and regional institutions need to become part of a decentralized network of biodiversity information facilities. GBIF and its many partners work to mobilize the data, and to improve search mechanisms, data and metadata standards, web services, and the other components of an Internet-based information infrastructure for biodiversity. GBIF makes available data that are shared by hundreds of data publishers from around the world. These data are shared according to the GBIF Data Use Agreement, which includes the provision that users of any data accessed through or retrieved via the GBIF Portal will always give credit to the original data publishers. * Explore Species: Find data for a species or other group of organisms. Information on species and other groups of plants, animals, fungi and micro-organisms, including species occurrence records, as well as classifications and scientific and common names. * Explore Countries: Find data on the species recorded in a particular country, territory or island. Information on the species recorded in each country, including records shared by publishers from throughout the GBIF network. * Explore Datasets: Find data from a data publisher, dataset or data network. Information on the data publishers, datasets and data networks that share data through GBIF, including summary information on 10028 datasets from 419 data publishers.

Proper citation: GBIF - Global Biodiversity Information Facility (RRID:SCR_005904) Copy   

•   Source: SciCrunch Registry

http://www.nextprot.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 15,2025. Human protein knowledge platform. Knowledge platform for human proteins selects and filters high throughput data pertinent to human proteins from UniProtKB. Extends UniProtKB/Swiss-Prot annotations for human proteins to include several new data types.

Proper citation: neXtProt (RRID:SCR_008911) Copy   

•   Source: SciCrunch Registry

http://harvester.fzk.de/harvester/

Harvester is a Web-based tool that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. It is a meta search engine for gene and protein information. It searches 16 major databases and prediction servers and combines the results on pregenerated HTML pages. In this way Harvester can provide comprehensive gene-protein information from different servers in a convenient and fast manner. As full text meta search engine, similar to Google trade mark, Harvester allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. Sponsors: This work has been supported by the BMBF with grants 01GR0101 and 01KW0013.

Proper citation: Bioinformatic Harvester IV (beta) at Karlsruhe Institute of Technology (RRID:SCR_008017) Copy   

•   Source: SciCrunch Registry

http://www.aniseed.cnrs.fr/

Database of ascidian embryonic development at the level of the genome (cis-regulatory sequences, gene expression, protein annotation), of the cell (morphology, fate, induction, lineage) or of the whole embryo (anatomy, morphogenesis). Currently, four organism models are described in Aniseed: Ciona intestinalis, Ciona savignyi, Halocynthia roretzi and Phallusia mammillata.
This version supports four sets of Ciona intestinalis transcript models: JGI v1.0, KyotoGrail 2005, KH and ENSEMBL, all functionally annotated, and grouped into Aniseedv3.0 gene models. Users can explore their expression profiles during normal or manipulated development, access validated cis-regulatory regions, get the molecular tools used to assay gene function, or all articles related to the function, or regulation of a given gene. Known transcriptional regulators and targets are listed for each gene, as are the gene regulatory networks acting in individual anatomical territories.
ANISEED is a community tool, and the direct involvement of external contributors is important to optimize the quality of the submitted data. Virtual embryo: The 3D Virtual embryo is available to download in the download section of the website.

Proper citation: Ascidian Network for InSitu Expression and Embryological Data (RRID:SCR_013030) Copy   

•   Source: SciCrunch Registry

http://www.physionet.org/

Collection of dissemination and exchange recorded biomedical signals and open-source software for analyzing them. Provides facilities for cooperative analysis of data and evaluation of proposed new algorithm. Providies free electronic access to PhysioBank data and PhysioToolkit software. Offers service and training via on-line tutorials to assist users at entry and more advanced levels. In cooperation with annual Computing in Cardiology conference, PhysioNet hosts series of challenges, in which researchers and students address unsolved problems of clinical or basic scientific interest using data and software provided by PhysioNet. All data included in PhysioBank, and all software included in PhysioToolkit, are carefully reviewed. Researchers are further invited to contribute data and software for review and possible inclusion in PhysioBank and PhysioToolkit. Please review guidelines before submitting material.

Proper citation: PhysioNet (RRID:SCR_007345) Copy   

•   Source: SciCrunch Registry

https://www.mcgill.ca/bic/resources/omega

Open data repository fully dedicated to MEG data in raw and processed form. The archive also contains anatomical MRI volumes and demographic and questionnaire information. Organized and stored as the Brain Imaging Data Structure (BIDS) with the integration of multimodal electrophysiology data. Directly readable by data-analysis software with Brainstorm. OMEGA will continue to expand, with contributions from the scientific community.

Proper citation: Open MEG Archive (RRID:SCR_014930) Copy   

•   Source: SciCrunch Registry

http://sideeffects.embl.de/

Database containing information on marketed medicines and their recorded adverse drug reactions. The information is extracted from public documents and package inserts. The available information include side effect frequency, drug and side effect classifications as well as links to further information, for example drug-target relations. The SIDER Side Effect Resource represents an effort to aggregate dispersed public information on side effects. To our knowledge, no such resource exist in machine-readable form despite the importance of research on drugs and their effects. The creation of this resource was motivated by the many requests for data that we received related to our paper (Campillos, Kuhn et al., Science, 2008, 321(5886):263-6.) on the utilization of side effects for drug target prediction. Inclusion of side effects as readouts for drug treatment should have many applications and we hope to be able to enhance the respective research with this resource. You may browse the drugs by name, browse the side effects by name, download the current version of SIDER, or use the search interface.

Proper citation: SIDER (RRID:SCR_004321) Copy   

•   Source: SciCrunch Registry