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http://lab.rockefeller.edu/tuschl/

RNA is not only a carrier of genetic information, but also a catalyst and a guide for sequence-specific recognition and processing of other RNA molecules. This lab investigates the regulatory mechanisms of RNA interference, RNA-mediated translational control, and nuclear pre-mRNA splicing. Classical and combinatorial biochemical techniques are used to analyze the function of the RNA- and protein-components involved in those processes.

Proper citation: Tuschl Laboratory: RNA Molecular Biology (RRID:SCR_002866) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/group/nusselab/cgi-bin/wnt/

A resource for members of the Wnt community, providing information on progress in the field, maps on signaling pathways, and methods. The page on reagents lists many resources generously made available to and by the Wnt community. Wnt signaling is discussed in many reviews and in a recent book. There are usually several Wnt meetings per year.

Proper citation: Wnt homepage (RRID:SCR_000662) Copy   

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http://gowiki.tamu.edu/wiki/

A wiki where users of the Gene Ontology can contribute and view notes about how specific GO terms are used. GONUTS can also be used as a GO term browser, or to search for GO annotations of specific genes from included organisms. The rationale for this wiki is based on helping new users of the gene ontology understand and use it. The GONUTS wiki is not an official product of the the Gene Ontology consortium. The GO consortium has a public wiki at their website, http://wiki.geneontology.org/. Maintaining the ontology involves many decisions to carefully choose terms and relationships. These decisions are currently made at GO meetings and via online discussion using the GO mailing lists and the Sourceforge curator request tracker. However, it is difficult for someone starting to use GO to understand these decisions. Some insight can be obtained by mining the tracker, the listservs and the minutes of GO meetings, but this is difficult, as these discussions are often dispersed and sometimes don't contain the GO accessions in the relevant messages. Wikis provide a way to create collaboratively written documentation for each GO term to explain how it should be used, how to satisfy the true path requirement, and whether an annotation should be placed at a different level. In addition, the wiki pages provide a discussion space, where users can post questions and discuss possible changes to the ontology. GONUTS is currently set up so anyone can view or search, but only registered users can edit or add pages. Currently registered users can create new users, and we are working to add at least one registered user for each participating database (So far we have registered users at EcoliHub, EcoCyc, GOA, BeeBase, SGD, dictyBase, FlyBase, WormBase, TAIR, Rat Genome Database, ZFIN, MGI, UCL and AgBase...

Proper citation: GONUTS (RRID:SCR_000653) Copy   

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http://www.bumc.bu.edu/cardiovascularproteomics/

The Cardiovascular Proteomics Center is a research center funded by the NIH/NHLBI to analyze and identify proteins that may be modified or created by oxidative stress. The CPC is developing and applying new proteomics methodology and instrumentation to the analysis of known proteins and those yet to be discovered.

Proper citation: Cardiovascular Proteomics Center (RRID:SCR_000603) Copy   

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https://medicine.yale.edu/keck/nida/yped/

Open source system for storage, retrieval, and integrated analysis of large amounts of data from high throughput proteomic technologies. YPED currently handles LCMS, MudPIT, ICAT, iTRAQ, SILAC, 2D Gel and DIGE. The repository contains data sets which have been released for public viewing and downloading by the responsible Primary Investigators. It includes proteomic data generated by the Yale NIDA Neuroproteomics Center (http://medicine.yale.edu/keck/nida/index.aspx). Sample descriptions are compatible with the evolving MIAPE standards.

Proper citation: YPED (RRID:SCR_001436) Copy   

•   Source: SciCrunch Registry

http://www.genome.jp/kegg/expression/

Database for mapping gene expression profiles to pathways and genomes. Repository of microarray gene expression profile data for Synechocystis PCC6803 (syn), Bacillus subtilis (bsu), Escherichia coli W3110 (ecj), Anabaena PCC7120 (ana), and other species contributed by the Japanese research community.

Proper citation: Kyoto Encyclopedia of Genes and Genomes Expression Database (RRID:SCR_001120) Copy   

•   Source: SciCrunch Registry

http://globin.cse.psu.edu/

Data and tools for studying the function of DNA sequences, with an emphasis on those involved in the production of hemoglobin. It includes information about naturally-occurring human hemoglobin mutations and their effects, experimental data related to the regulation of the beta-like globin gene cluster, and software tools for comparing sequences with one another to discover regions that are likely to play significant roles.

Proper citation: Globin Gene Server (RRID:SCR_001480) Copy   

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http://amp.pharm.mssm.edu/Enrichr/

A web-based gene list enrichment analysis tool that provides various types of visualization summaries of collective functions of gene lists. It includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes / proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries.

Proper citation: Enrichr (RRID:SCR_001575) Copy   

•   Source: SciCrunch Registry

http://cshprotocols.cshlp.org/cgi/collection/behavioral_assays

A bibliography of published Behavioral Assays by Cold Spring Harbor Protocols. Cold Spring Harbor Protocols is an interdisciplinary journal providing a definitive source of research methods in cell, developmental and molecular biology, genetics, bioinformatics, protein science, computational biology, immunology, neuroscience and imaging. Each monthly issue details multiple essential methods - a mix of cutting-edge and well-established techniques. Newly commissioned protocols and unsolicited submissions are supplemented with articles based on Cold Spring Harbor Laboratorys renowned courses and manuals. All protocols are up-to-date and presented in a consistent, easy-to-follow format.

Proper citation: Cold Spring Harbor Protocols: Collected Resources - Behavioral Assays (RRID:SCR_001697) Copy   

•   Source: SciCrunch Registry

http://ilyinlab.org/friend/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Friend is a bioinformatics application designed for simultaneous analysis and visualization of multiple structures and sequences of proteins and/or DNA/RNA. The application provides basic functionalities such as: structure visualization with different rendering and coloring, sequence alignment, and simple phylogeny analysis, along with a number of extended features to perform more complex analyses of sequence structure relationships, including: structural alignment of proteins, investigation of specific interaction motifs, studies of protein-protein and protein-DNA interactions, and protein super-families. Friend is also useful for the functional annotation of proteins, protein modeling, and protein folding studies. Friend provides three levels of usage; 1) an extensive GUI for a scientist with no programming experience, 2) a command line interface for scripting for a scientist with some programming experience, and 3) the ability to extend Friend with user written libraries for an experienced programmer. The application is linked and communicates with local and remote sequence and structure databases.

Proper citation: An Integrated Multiple Structure Visualization and Multiple Sequence Alignment Application (RRID:SCR_001646) Copy   

•   Source: SciCrunch Registry

http://silac.org/

Stable isotope labeling with amino acids in cell culture (SILAC) is a simple and straightforward approach for in vivo incorporation of a label into proteins for mass spectrometry (MS)-based quantitative proteomics. SILAC relies on metabolic incorporation of a given "light" or "heavy" form of the amino acid into the proteins. The method relies on the incorporation of amino acids with substituted stable isotopic nuclei (e.g. deuterium, 13C, 15N). In an experiment, two cell populations are grown in culture media that are identical except that one of them contains a "light" and the other a "heavy" form of a particular amino acid (e.g. 12C and 13C labeled L-lysine, respectively). When the labeled analog of an amino acid is supplied to cells in culture instead of the natural amino acid, it is incorporated into all newly synthesized proteins. After a number of cell divisions, each instance of this particular amino acid will be replaced by its isotope labeled analog. Since there is hardly any chemical difference between the labeled amino acid and the natural amino acid isotopes, the cells behave exactly like the control cell population grown in the presence of normal amino acid. It is efficient and reproducible as the incorporation of the isotope label is 100%. SILAC Applications: - Differential expression of proteins and identification of disease biomarkers - Cell signaling dynamics - Analysis of yeast pheromone signaling pathway - Identification of methylation sites - Identification of protease substrates - Study of protein complexes/protein interactions - Analysis of signaling pathways and effect of pharmacological inhibitors - Subcellular proteomics Sponsors: Supported in part by an NIH Roadmap grant Technology Center for Networks & Pathways of Lysine Modification.

Proper citation: Stable Isotope Labeling with Amino Acids in Cell Culture (RRID:SCR_001873) Copy   

•   Source: SciCrunch Registry

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

The UCLA-DOE Institute for Genomics and Proteomics carries out research in bioenergy, structural biology, genomics and proteomics, consistent with the research mission of the United States Department of Energy. Major interests of the 12 Principal Investigators and 9 Associate Members include systems approaches to organisms, structural biology, bioinformatics, and bioenergetic systems. The Institute sponsors 5 Core Technology Centers, for X-ray and NMR structural determination, bioinformatics and computation, protein expression and purification, and biochemical instrumentation. Services offered by this Institute: - Databases: * DIP (The Database of Interacting Proteins): The DIPTM database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions. * ProLinks Database of Functional Linkages: The Prolinks database is a collection of inference methods used to predict functional linkages between proteins. These methods include the Phylogenetic Profile method which uses the presence and absence of proteins across multiple genomes to detect functional linkages; the Gene Cluster method, which uses genome proximity to predict functional linkage; Rosetta Stone, which uses a gene fusion event in a second organism to infer functional relatedness; and the Gene Neighbor method, which uses both gene proximity and phylogenetic distribution to infer linkage. - Data-to-Structure Servers: * SAVEs Structure Verification Server * Merohedral Twinning Test Server * SER Surface Entropy Reduction Server * VERIFY3D Structure Verification Server * ERRAT Structure Verification Server - Structure-to-Function Servers: * ProKnow Protein Functionator * Hot Patch Functional Site Locator

Proper citation: University of California at Los Angeles - Department of Energy Institute for Genomics and Proteomics (RRID:SCR_001921) Copy   

•   Source: SciCrunch Registry

http://meme-suite.org/

Suite of motif-based sequence analysis tools to discover motifs using MEME, DREME (DNA only) or GLAM2 on groups of related DNA or protein sequences; search sequence databases with motifs using MAST, FIMO, MCAST or GLAM2SCAN; compare a motif to all motifs in a database of motifs; associate motifs with Gene Ontology terms via their putative target genes, and analyze motif enrichment using SpaMo or CentriMo. Source code, binaries and a web server are freely available for noncommercial use.

Proper citation: MEME Suite - Motif-based sequence analysis tools (RRID:SCR_001783) Copy   

•   Source: SciCrunch Registry

http://tigger.uic.edu/~cjeffery/

The moonlighting protein database is not yet available publicly. Stay tuned. Moonlighting proteins have multiple, seemingly unrelated functions not due to gene fusions or alternative splicing. Like PGI, which is a cytosolic enzyme and an extracellular cytokine, dozens of other proteins have been found to moonlight. Connie coined the term moonlighting proteins and has written several review articles that develop the idea of moonlighting proteins and describe additional moonlighting proteins from the literature, how they switch between functions, how they might have evolved, and how they might benefit the cell. She is currently writing two additional invited articles and planning computational studies of the sequences and structures of known moonlighting proteins.

Proper citation: MoonProt (RRID:SCR_008803) Copy   

•   Source: SciCrunch Registry

http://clipserve.clip.ubc.ca/topfind

An integrated knowledgebase focused on protein termini, their formation by proteases and functional implications. It contains information about the processing and the processing state of proteins and functional implications thereof derived from research literature, contributions by the scientific community and biological databases. It lists more than 120,000 N- and C-termini and almost 10,000 cleavages. TopFIND is a resource for comprehensive coverage of protein N- and C-termini discovered by all available in silico, in vitro as well as in vivo methodologies. It makes use of existing knowledge by seamless integration of data from UniProt and MEROPS and provides access to new data from community submission and manual literature curating. It renders modifications of protein termini, such as acetylation and citrulination, easily accessible and searchable and provides the means to identify and analyse extend and distribution of terminal modifications across a protein. The data is presented to the user with a strong emphasis on the relation to curated background information and underlying evidence that led to the observation of a terminus, its modification or proteolytic cleavage. In brief the protein information, its domain structure, protein termini, terminus modifications and proteolytic processing of and by other proteins is listed. All information is accompanied by metadata like its original source, method of identification, confidence measurement or related publication. A positional cross correlation evaluation matches termini and cleavage sites with protein features (such as amino acid variants) and domains to highlight potential effects and dependencies in a unique way. Also, a network view of all proteins showing their functional dependency as protease, substrate or protease inhibitor tied in with protein interactions is provided for the easy evaluation of network wide effects. A powerful yet user friendly filtering mechanism allows the presented data to be filtered based on parameters like methodology used, in vivo relevance, confidence or data source (e.g. limited to a single laboratory or publication). This provides means to assess physiological relevant data and to deduce functional information and hypotheses relevant to the bench scientist. TopFIND PROVIDES: * Integration of protein termini with proteolytic processing and protein features * Displays proteases and substrates within their protease web including detailed evidence information * Fully supports the Human Proteome Project through search by chromosome location CONTRIBUTE * Submit your N- or C-termini datasets * Contribute information on protein cleavages * Provide detailed experimental description, sample information and raw data

Proper citation: TopFIND (RRID:SCR_008918) Copy   

•   Source: SciCrunch Registry

http://www.pdbj.org/

PDBj (Protein Data Bank Japan) maintains a centralized PDB archive of macromolecular structures and provides integrated tools, in collaboration with the RCSB, the BMRB in USA and the PDBe in EU.

Proper citation: PDBj - Protein Data Bank Japan (RRID:SCR_008912) Copy   

•   Source: SciCrunch Registry

http://apid.dep.usal.es

APID Interactomes (Agile Protein Interactomes DataServer) provides information on the protein interactomes of numerous organisms, based on the integration of known experimentally validated protein-protein physical interactions (PPIs). The interactome data includes a report on quality levels and coverage over the proteomes for each organism included. APID integrates PPIs from primary databases of molecular interactions (BIND, BioGRID, DIP, HPRD, IntAct, MINT) and also from experimentally resolved 3D structures (PDB) where more than two distinct proteins have been identified. This collection references protein interactors, through a UniProt identifier.

Proper citation: Agile Protein Interactomes DataServer (RRID:SCR_008871) Copy   

•   Source: SciCrunch Registry

http://pathways.mcdb.ucla.edu/algal/

Tools to search gene lists for functional term enrichment as well as to dynamically visualize proteins onto pathway maps. Additionally, integrated expression data may be used to discover similarly expressed genes based on a starting gene of interest.

Proper citation: Algal Functional Annotation Tool (RRID:SCR_012034) Copy   

•   Source: SciCrunch Registry

http://www.jiffynet.org/

Web based instant protein network modeler for newly sequenced species. Web server designed to instantly construct genome scale protein networks using protein sequence data. Provides network visualization, analysis pages and solution for instant network modeling of newly sequenced species.

Proper citation: JiffyNet (RRID:SCR_011954) Copy   

•   Source: SciCrunch Registry

http://wiki.c2b2.columbia.edu/califanolab/index.php/BCellInteractome.htm

A network of protein-protein, protein-DNA and modulatory interactions in human B cells. The network contains known interactions (reported in public databases) and predicted interactions by a Bayesian evidence integration framework which integrates a variety of generic and context specific experimental clues about protein-protein and protein-DNA interactions with inferences from different reverse engineering algorithms, such as GeneWays and ARACNE. Modulatory interactions are predicted by the MINDY, an algorithm for the prediction of modulators of transcriptional interactions (please refer to the publication section for more information). The BCI can be downloaded as one tab delimited file containing the complete network (BCI.txt) with each type of interaction explicitly defined.

Proper citation: B Cell Interactome (RRID:SCR_008655) Copy   

•   Source: SciCrunch Registry