Tools   Select Another Resource Report Type

http://www.ccp4.ac.uk/

Portal for Macromolecular X-Ray Crystallography to produce and support an integrated suite of programs that allows researchers to determine macromolecular structures by X-ray crystallography, and other biophysical techniques. Used in the education and training of scientists in experimental structural biology for determination and analysis of protein structure.

Proper citation: CCP4 (RRID:SCR_007255) Copy   

•   Source: SciCrunch Registry

https://cgc.umn.edu

Center that acquires, maintains, and distributes genetic stocks and information about stocks of the small free-living nematode Caenorhabditis elegans for use by investigators initiating or continuing research on this genetic model organism. A searchable strain database, general information about C. elegans, and links to key Web sites of use to scientists, including WormBase, WormAtlas, and WormBook are available.

Proper citation: Caenorhabditis Genetics Center (RRID:SCR_007341) Copy   

•   Source: SciCrunch Registry

http://braintrap.inf.ed.ac.uk/braintrap/

This database contains information on protein expression in the Drosophila melanogaster brain. It consists of a collection of 3D confocal datasets taken from EYFP expressing protein trap Drosophila lines from the Cambridge Protein Trap project. Currently there are 884 brain scans from 535 protein trap lines in the database. Drosophila protein trap strains were generated by the St Johnston Lab and the Russell Lab at the University of Cambridge, UK. The piggyBac insertion method was used to insert constructs containing splice acceptor and donor sites, StrepII and FLAG affinity purification tags, and an EYFP exon (Venus). Brain images were acquired by Seymour Knowles-Barley, in the Armstrong Lab at the University of Edinburgh. Whole brain mounts were imaged by confocal microscopy, with a background immunohistochemical label added to aid the identification of brain structures. Additional immunohistochemical labeling of the EYFP protein using an anti-GFP antibody was also used in most cases. The trapped protein signal (EYFP / anti-GFP), background signal (NC82 label), and the merged signal can be viewed on the website by using the corresponding channel buttons. In all images the trapped protein / EYFP signal appears green and the background / NC82 channel appears magenta. Original .lsm image files are also available for download.

Proper citation: BrainTrap: Fly Brain Protein Trap Database (RRID:SCR_003398) Copy   

•   Source: SciCrunch Registry

http://brainarray.mbni.med.umich.edu/Brainarray/Database/ProbeMatchDB/ncbi_probmatch_para_step1.asp

Matches a list of microarray probes across different microrarray platforms (GeneChip, EST from different vendors, Operon Oligos) and species (human, mouse and rat), based on NCBI UniGene and HomoloGene. The capability to match protein sequence IDs has just been added to facilitate proteomic studies. The ProbeMatchDB is mainly used for the design of verification experiments or comparing the microarray results from different platforms. It can be used for finding equivalent EST clones in the Research Genetics sequence verified clone set based on results from Affymetirx GeneChips. It will also help to identify probes representing orthologous genes across human, mouse and rat on different microarray platforms.

Proper citation: ProbeMatchDB 2.0 (RRID:SCR_003433) Copy   

•   Source: SciCrunch Registry

http://prosite.expasy.org/

Database of protein families and domains that is based on the observation that, while there is a huge number of different proteins, most of them can be grouped, on the basis of similarities in their sequences, into a limited number of families. Proteins or protein domains belonging to a particular family generally share functional attributes and are derived from a common ancestor. It is complemented by ProRule, a collection of rules based on profiles and patterns, which increases the discriminatory power of profiles and patterns by providing additional information about functionally and/or structurally critical amino acids. ScanProsite finds matches of your protein sequences to PROSITE signatures. PROSITE currently contains patterns and profiles specific for more than a thousand protein families or domains. Each of these signatures comes with documentation providing background information on the structure and function of these proteins. The database is available via FTP.

Proper citation: PROSITE (RRID:SCR_003457) Copy   

•   Source: SciCrunch Registry

http://www.thesgc.org/

Charity registered in United Kingdom whose mission is to accelerate research in new areas of human biology and drug discovery.Not for profit, public-private partnership that carries out basic science of relevance to drug discovery whose core mandate is to determine 3D structures on large scale and cost effectively targeting human proteins of biomedical importance and proteins from human parasites that represent potential drug targets.

Proper citation: Structural Genomics Consortium (RRID:SCR_003890) Copy   

•   Source: SciCrunch Registry

http://www.pharma-planta.net/

Consortium to develop efficient and safe strategies for the production of clinical-grade protein pharmaceuticals in plants, and to define the procedures needed for the production of these proteins in compliance with the strict regulatory standards that govern the manufacture of all pharmaceuticals. Ultimately the consortium aimed to take a candidate product all the way through the development pipeline culminating in a phase I human clinical trial. The consortium has a wide range of expertise spanning the areas of molecular biology, plant biology, immunology, recombinant protein expression technology, vaccinology, and plant biotechnology. The objectives listed at the beginning of the Pharma-Planta project are as follows: # To produce a recombinant pharmaceutical molecule in transgenic plants, which will be developed through all regulatory requirements, GMP (good manufacturing practice) standards and pre-clinical toxicity testing. This will then be evaluated in Phase I human clinical trials. # To develop robust risk assessment practices for recombinant pharmaceutical molecules produced in plants, based on health and environmental impact, working with regulatory authorities within the EU as well as public groups to ensure that the production systems are as safe and as acceptable as possible, and that they comply with all biosafety regulations. # To define and carry out a coordinated program for securing and managing intellectual property that will facilitate the availability of high priority plant-derived recombinant pharmaceuticals to the poor in developing countries while simultaneously allowing the products to be developed commercially in Europe and North America. # To develop and refine new strategies for the expression of recombinant pharmaceuticals in plants, which can be used on a generic basis for molecules that are normally expressed poorly. # To develop and generate transgenic plants expressing a second generation of recombinant molecules that will be used in future clinical trials. In 2011 they reached their benchmark for success launching a phase I clinical study of an antibody that neutralizes HIV, produced in and isolated from tobacco plants. This antibody could one day become an inexpensive component of a microbicide used to prevent the spread of HIV/AIDS. The project has also spun off many additional technologies that are being adopted by researchers all over the world, and has resulted in more than 100 publications in peer-reviewed scientific journals.

Proper citation: Pharma-Planta Consortium (RRID:SCR_003880) Copy   

•   Source: SciCrunch Registry

http://www.wholecellkb.org/

A collection of free, open-source model organism databases designed specifically to enable comprehensive, dynamic simulations of entire cells and organisms. WholeCellKB provides comprehensive, quantitative descriptions of individual species including: * Their subcellular organization, * Their chromosome sequences, * The essentiality, location, length, direction, and homologs of each gene, * The organization and promoter of each transcription unit, * The expression and degradation rate of each RNA gene product, * The specific folding and maturation pathway of each RNA and protein species including the localization, N-terminal cleavage, signal sequence, prosthetic groups, disulfide bonds, and chaperone interactions of each protein species, * The subunit composition of each macromolecular complex, * Their genetic code, * The binding sites and footprint of every DNA-binding protein, * The structure, charge, and hydrophobicity of every metabolite, * The stoichiometry, catalysis, coenzymes, energetics, and kinetics of every chemical reaction, * The regulatory strength of each transcription factor on each promoter, * Their chemical composition, and * The composition of its typical SP-4 laboratory growth medium. WholeCellKB currently contains a single database of Mycoplasma genitalium, an extremely small gram-positive bacterium and common human pathogen. This database is the most comprehensive description of any single organism to date, and was used to develop the first whole-cell computational model. Users can download the WholeCellKB source code and content to create and customize - including the content, data model, and user interface - their own model organism database.

Proper citation: WholeCellKB (RRID:SCR_004104) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/pdbe/

The European resource for the collection, organization and dissemination of data on biological macromolecular structures. In collaboration with the other worldwide Protein Data Bank (wwPDB) partners - the Research Collaboratory for Structural Bioinformatics (RCSB) and BioMagResBank (BMRB) in the USA and the Protein Data Bank of Japan (PDBj) - they work to collate, maintain and provide access to the global repository of macromolecular structure data. The main objectives of the work at PDBe are: * to provide an integrated resource of high-quality macromolecular structures and related data and make it available to the biomedical community via intuitive user interfaces. * to maintain in-house expertise in all the major structure-determination techniques (X-ray, NMR and EM) in order to stay abreast of technical and methodological developments in these fields, and to work with the community on issues of mutual interest (such as data representation, harvesting, formats and standards, or validation of structural data). * to provide high-quality deposition and annotation facilities for structural data as one of the wwPDB deposition sites. Several sophisticated tools are also available for the structural analysis of macromolecules.

Proper citation: PDBe - Protein Data Bank in Europe (RRID:SCR_004312) Copy   

•   Source: SciCrunch Registry

http://www.science.mcmaster.ca/biochem/faculty/truant/truantlab.htm

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 21, 2013. Laboratory portal of Ray Truant, PhD. It provides an image gallery and videos.

Proper citation: Ray Truant Lab (RRID:SCR_004301) Copy   

•   Source: SciCrunch Registry

http://blast.ncbi.nlm.nih.gov/Blast.cgi

Web search tool to find regions of similarity between biological sequences. Program compares nucleotide or protein sequences to sequence databases and calculates statistical significance. Used for identifying homologous sequences.

Proper citation: NCBI BLAST (RRID:SCR_004870) Copy   

•   Source: SciCrunch Registry

http://noble.gs.washington.edu/proj/philius/

Web server that predicts protein transmembrane topology and signal peptides. Hidden Markov models (HMM) have been successfully applied to the tasks of transmembrane protein topology prediction and signal peptide prediction. They expand upon this work by making use of the more powerful class of dynamic Bayesian networks (DBN). Their model, Philius, is inspired by a previously published HMM, Phobius, and combines a signal peptide sub-model with a transmembrane sub-model. They introduce a two-stage DBN decoder which combines the power of posterior decoding with the grammar constraints of Viterbi-style decoding. Philius also provides protein type, segment, and topology confidence metrics to aid in the interpretation of the predictions.

Proper citation: Philius (RRID:SCR_004625) Copy   

•   Source: SciCrunch Registry

http://www.pantherdb.org/

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   

•   Source: SciCrunch Registry

http://www.proteopedia.org/

Free, collaborative 3D, interactive encyclopedia of proteins and other molecules, it collects, organizes and disseminates structural and functional knowledge about protein, RNA, DNA, and other macromolecules, and their assemblies and interactions with small molecules, in a manner that is relevant and broadly accessible to students and scientists. With a free user account, users can edit pages in Proteopedia. Click on the green links to change the 3D image or click and drag the molecules. Categories include Diseases & Related Topics, Enzymes, Gene Expression & Replication, Metabolism, Signaling & Transport, Structural Biology and Miscellaneous. Currently, Proteopedia has 93,912 articles (pages), and 2,366 registered users (May 2013). Among other pages, Proteopedia contains one page (or article) for every entry in the World Wide Protein Data Bank. Proteopedia is updated weekly with new entries shortly after they are released by the Protein Data Bank. Most of these pages, which are titled with a four-character PDB identification code, are seeded automatically to include a default view of the asymmetric unit, the abstract of the publication, green links to sites and ligands, and molecule-specific links to other viewers and databases. When you go to a random page, you nearly always get one of these automatically-seeded, PDB-code-titled pages (click Random Page in the navigation box at the upper left), because of their abundance. In addition to one article about each entry in the Protein Data Bank (PDB identification code-titled articles), there are articles titled with the name of a molecule or a subject, instead of a PDB identification code. Some of these articles that have substantial content are listed at Topic Pages, or you can browse a complete list of articles not titled with a PDB identification code. There are also articles About Macromolecular Structure.

Proper citation: Proteopedia - Life in 3D (RRID:SCR_004647) Copy   

•   Source: SciCrunch Registry

http://smart.embl.de/

Software tool for identification and annotation of genetically mobile domains and analysis of domain architectures.

Proper citation: SMART (RRID:SCR_005026) Copy   

•   Source: SciCrunch Registry

http://sybil.sourceforge.net/

A web-based software package for comparative genomics.

Proper citation: Sybil (RRID:SCR_005593) Copy   

•   Source: SciCrunch Registry

http://edwardslab.bmcb.georgetown.edu/ws/peptideMapper/

The PeptideMapper Web-Service provides alignments of peptide sequence alignments to proteins, mRNA, EST, and HTC sequences from Genbank, RefSeq, UniProt, IPI, VEGA, EMBL, and HInvDb. This mapping infrastructure is supported, in part, by the compressed peptide sequence database infrastructure (Edwards, 2007) which enables a fast, suffix-tree based mapping of peptide sequences to gene identifiers and a gene-focused detailed mapping of peptide sequences to source sequence evidence. The PeptideMapper Web-Service can be used interactively or as a web-service using either HTTP or SOAP requests. Results of HTTP requests can be returned in a variety of formats, including XML, JSON, CSV, TSV, or XLS, and in some cases, GFF or BED; results of SOAP requests are returned as SOAP responses. The PeptideMapper Web-Service maps at most 20 peptides with length between 5 and 30 amino-acids in each request. The number of alignments returned, per peptide, gene, and sequence type, is set to 10 by default. The default can be changed on the interactive alignments search form or by using the max web-service parameter.

Proper citation: PeptideMapper (RRID:SCR_005763) Copy   

•   Source: SciCrunch Registry

http://www.topsan.org/

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   

•   Source: SciCrunch Registry

http://fields.scripps.edu/

Scientists at the Yates Lab at The Scripps Research Institute (TSRI) rely on information yielded by tandem mass spectrometry to identify proteins from complex mixtures. Using this powerful technique, researchers draw upon a cross section of fields to increase the scope, sensitivity, and throughput of technologies for practical proteomics. Biologists provide the questions that drive our research. By identifying complexes that are poorly understood or organism-wide issues requiring further exploration, we gain a theoretical understanding of issues that are tractable only through proteomic strategies. Analytical chemists and biochemists improve our tools for revealing the proteins present in biological samples. Targets for optimization include the isolations used to obtain proteins, the steps to generate peptides from these proteins, and the separation of peptides en route to the mass spectrometer. Chemistry is vital to increasing power of proteomic technology. Computer science yields tools on two scales. First, the sequence corresponding to each peptide''s tandem mass spectrum must be identified. Once those identifications have been completed, additional tools are needed to summarize and organize these identifications.

Proper citation: TSRI-Yates Lab (RRID:SCR_005699) Copy   

•   Source: SciCrunch Registry

http://www.clipz.unibas.ch/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 20,2019.Database and analysis environment for experimentally determined binding sites of RNA-binding proteins. It supports the automatic functional annotation of short reads resulting primarily from crosslinking and immunoprecipitation experiments (CLIP) performed with RNA-binding proteins in order to identify the binding sites of these proteins. The functional annotation could be also applied to short reads resulting from other types of experiments such as mRNA-Seq, Digital Gene Expression, small RNA cloning, etc. The platform enables visualization and mining of individual data sets as well as analysis involving multiple experimental data sets. The platform can support collaborative projects involving multiple users and groups of users as well as public and private datasets.

Proper citation: CLIPZ (RRID:SCR_005755) Copy   

•   Source: SciCrunch Registry