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http://nrresource.org

Collection of individual databases on members of the steroid and thyroid hormone receptor superfamily. Although the databases are located on different servers and are managed individually, they each form a node of the NRR. The NRR itself integrates the separate databases and allows an interactive forum for the dissemination of information about the superfamily. NRR Components: Androgen receptor, Estrogen receptor, Glucocorticoid receptor, Peroxisome proliferator, Steroid receptor protein, Thyroid receptor, Vitamin D receptor.

Proper citation: Nuclear Receptor Resource (RRID:SCR_003285) 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.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.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.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://sift.bii.a-star.edu.sg/

Data analysis service to predict whether an amino acid substitution affects protein function based on sequence homology and the physical properties of amino acids. SIFT can be applied to naturally occurring nonsynonymous polymorphisms and laboratory-induced missense mutations. (entry from Genetic Analysis Software) Web service is also available.

Proper citation: SIFT (RRID:SCR_012813) Copy   

•   Source: SciCrunch Registry

https://github.com/macs3-project/MACS

Software Python package for identifying transcript factor binding sites. Used to evaluate significance of enriched ChIP regions. Improves spatial resolution of binding sites through combining information of both sequencing tag position and orientation. Can be used for ChIP-Seq data alone, or with control sample with increase of specificity.

Proper citation: MACS (RRID:SCR_013291) Copy   

•   Source: SciCrunch Registry

http://bioinfo.eie.polyu.edu.hk/mGoaSvmServer/mGOASVM.html

Data analysis service for the prediction of multi-label protein subcellular localization based on gene ontology and support vector machines. Web services are also available.

Proper citation: mGOASVM (RRID:SCR_013098) Copy   

•   Source: SciCrunch Registry

http://genetics.bwh.harvard.edu/pph2/

Software tool which predicts possible impact of amino acid substitution on structure and function of human protein using straightforward physical and comparative considerations. PolyPhen-2 is new development of PolyPhen tool for annotating coding nonsynonymous SNPs.

Proper citation: PolyPhen: Polymorphism Phenotyping (RRID:SCR_013189) Copy   

•   Source: SciCrunch Registry

http://xin.cz3.nus.edu.sg/group/admeap/admeap.asp

A database for facilitating the search for drug Absorption, Distribution, Metabolism, Excretion (ADME) associated proteins. It contains information about known drug ADME associated proteins, functions, similarities, substrates / ligands, tissue distributions, and other properties of the targets. Associated references are also included. Drug absorption, distribution, metabolism and excretion (ADME) often involve interaction of a drug with specific proteins. Knowledge about these ADME-associated proteins is important in facilitating the study of the molecular mechanism of disposition and individual response as well as therapeutic action of drugs. It is also useful in the development and testing of pharmacokinetics prediction tools. Several databases describing specific classes of ADME-associated proteins have appeared. A new database, ADME-associated proteins (ADME-AP), is introduced to provide comprehensive information about all classes of ADME-associated proteins described in the literature including physiological function of each protein, pharmacokinetic effect, ADME classification, direction and driving force of disposition, location and tissue distribution, substrates, synonyms, gene name and protein availability in other species. Cross-links to other databases are also provided to facilitate the access of information about the sequence, 3D structure, function, polymorphisms, genetic disorders, nomenclature, ligand binding properties and related literatures of each protein. ADME-AP currently contains entries for 321 proteins and 964 substrates. ADME Class Based on their respective role of pharmacokinetics, ADME-associated proteins can be classified into four categories: A: This Category includes proteins involved in the absorption or re-absorption of drugs into systemic system. D: This category includes proteins responsible for facilitating the distribution of drugs from the systemic system to the target sites or away from the target sites back to the systemic system. Certain plasma proteins and intracellular binding proteins may alter free drug concentration by acting as drug storage depot. These proteins thus play a regulatory role in drug distribution and they are thus included in Category D. Based on their role in drug distribution, proteins in this category can be further divided into three groups D1, D2, and D3. The first group D1 includes transporters capable of transporting chemicals across membranes of various tissue barriers from the systemic system into the target sites. Blood-brain barrier and placenta barrier are examples of tissue barrier. Proteins in the second group D2 are responsible for transporting drugs back into the systemic system. Proteins in the third group D3 mainly function as drug storage depot. These include ligand binding proteins in plasma and intracellular proteins. M: Proteins in category M are drug-metabolizing enzymes. These enzymes can be further divided into two separate groups M1 and M2, according to whether the corresponding enzymatic reaction is phase I or phase II. E: This category E includes proteins that enable the excretion or presystemic elimination of drugs. Some proteins belong to more than one category: e.g. P-glycoprotein both limits intestinal absorption and excludes drugs from the brain back to the blood. It thus belongs to both Category E and D. For those proteins capable of transporting natural substrates without literature report of interaction with a drug, a postfix potential is attached to their respective classification to indicate that their specific role in ADME is yet to be confirmed. Use of ADME-AP for commercial purposes is not allowed.

Proper citation: Drug ADME Associated Protein Database (RRID:SCR_013501) Copy   

•   Source: SciCrunch Registry

http://gpcr.usc.edu/#nogo

A protein family specific platform that works closely with the GPCR community to determine the high resolution structure and function of GPCRs. Structures are available in the glutamate, secretin, frizzled/TAS2, adhesion, and rhodopsin branches of the protein phylogenetic tree. Users can access a list of protein structure targets and completed protein structures.

Proper citation: GPCR Network (RRID:SCR_014286) Copy   

•   Source: SciCrunch Registry

http://www.matrixscience.com/server.html

A software package and server used to identify and characterize proteins from primary sequence databases using mass spectrometry data. Mascot integrates peptide mass fingerprinting, sequence querying, and MS/MS ion searching in order to search for proteins in databases like SwissProt, NCBInr, EMBL EST divisions, contaminants, and cRAP. If a license is purchased, users may: search data sets that exceed the 1200 spectrum limit of the free version; set up automated, high throughput work; add and edit proteins and quantification methods; and search a preferred collection of sequence databases. The software package works with instruments from AB Sciex, Agilent, Bruker, Jeol, Shimadzu, Thermo Scientific, and Waters.

Proper citation: Mascot (RRID:SCR_014322) Copy   

•   Source: SciCrunch Registry