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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

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  • RRID:SCR_014914

    This resource has 10+ mentions.

http://www.bioclipse.net/

Open source downloadable application which contains a framework for managing and analyzing chemical compounds, as well as supports editing in 2D, processing large collections of molecules in tables, calculate various types of properties, and more cheminformatics functionality. This software also is used for the management and analysis of biological sequences (DNA, RNA, and protein), and relates the chemical structures and a target and then describes them using mathematical descriptors and models them using statistical methods. Bioclipse is equipped with a scripting language (Bioclipse Scripting Language or BSL) which can be used to automate tasks or create reusable snippets that can be shared with others,

Proper citation: Bioclipse (RRID:SCR_014914) Copy   


  • RRID:SCR_000465

http://www.ispybio.com/

Search engine for Life scientists that ranks reagents by the amount of data available, such as publications, reviews, characterization images and tested applications. It displays reagents such as antibodies, proteins, ELISA kits and biomolecules. Its proprietary search algorithm is unique and rapidly analyzes the end-user's search query against its large database, while powerful filters allow the user to enhance search results. As iSpyBio syncs with supplier and other public databases, it is always up-to-date - allowing iSpyBio to exclude out of stock items, whilst also showing the most recent testing results and peer-reviewed publications.

Proper citation: iSpyBio.com (RRID:SCR_000465) Copy   


http://crbs.ucsd.edu/

CRBS is a UCSD organized research unit (ORU) that exists to provide human resources, high technology equipment, and administrative services to researchers engaged in fundamental research on cell structure and function relationships in central nervous system processes, cardiovascular networking, and muscular contraction through multiple scales and modalities. CRBS scientists investigate these processes through invention, refinement, and deployment of sophisticated technologies, especially: - High-powered electron microscopes that reveal three-dimensional cell structures - State-of-the-art X-ray crystallography and magnetic resonance analysis that provide detail on protein structures at high-resolution - Laser-scanning and confocal light microscopes that reveal molecules tagged with fluorescent markers as they traffic within cells and pass transfer signals within and between cells - High performance computing and grid-based integration of distributed data CRBS facilitates an interdisciplinary infrastructure in which people from biology, medicine, chemistry, and physics can work with those from computer science and information technologies in collaborative research. Researchers share interests in the study of complex biological systems at many scales, from the structures of enzymes, proteins, and the body's chemical communications network at atomic and molecular levels, to an organism's physiology, strength, and support at cellular and tissue levels. The CRBS infrastructure integrates resources for high-performance computing, visualization, and database technologies, and the grid-integration of large amounts of archival storage data. The California Institute for Telecommunications and Information Technology (Cal-IT2) and the San Diego Supercomputer Center (SDSC) are collaborators in simulating the activity of biological systems, analyzing the results, and organizing the growing storehouse of biological information. CRBS is an entity evolving as research evolves. It forges interactions with biotechnology and biocomputing companies for technology transfer. Interaction, collaboration, and multiscale research produce new perspectives, reveal fruitful research topics, lead to the development of new technologies and drugs, and train a new generation of researchers in biological systems. Sponsors: CRBS is supported by the University of California at San Diego.

Proper citation: Center for Research in Biological Systems (RRID:SCR_002666) Copy   


  • RRID:SCR_005675

    This resource has 100+ mentions.

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

Software program that automatically annotates a protein list with information that helps in the meaningful interpretation of data from mass spectrometry and other techniques. It takes protein lists as input, in the form of plain text files, protXML files (usually from the TPP), or Dat files from MASCOT search results. From this, it generates protein annotation tables, and a variety of GO charts to aid individual and differential analysis of proteomics data. It downloads information from mainly the Uniprot and EBI QuickGO databases. STRAP requires Windows XP or higher with at least version 3.5 of the Microsoft .NET Framework installed. Platform: Windows compatible

Proper citation: STRAP (RRID:SCR_005675) Copy   


http://hcc.musc.edu/research/resources/biorepository/

The Hollings Cancer Center Tissue Biorepository & Research Pathology Services Shared Resource provides investigators with a centralized infrastructure that promotes biomedical research involving the use and study of human biospecimens. The shared resource is comprised of four integrated components: Biospecimens and data bank, Laser Capture Microdissection, Tissue Microarray, and Research Pathology Services. These components, along with extensive staff expertise, offer a comprehensive means by which researchers can utilize valuable human biospecimens and cutting edge technology to support basic, translational and clinical research. Services: * Biospecimen and Data Bank ** Collecting, processing, and banking of tissue, saliva, urine, blood, plasma, serum, and other tissue derivatives; including those for protocol driven studies ** Retrieval of banked specimens linked to clinicopathologic data, while maintaining patient confidentiality, for research use ** Quality control of collected tissue by the Tissue Biorepository Director, a trained pathologist: verification of diseased state and assessment of tumor purity, etc ** Quality control of DNA/RNA/protein isolated from collected tissue using the Agilent Bioanalyzer * Laser Capture Microdissection ** Identification, localization, and microdissection of targeted cell populations (from human and animal tissue sources) ** Extraction of DNA/RNA/protein from microdissected samples. ** Quality analysis and quality control of isolated nucleic acid using Agilent Bioanalyzer * Tissue Microarray ** Create custom and standard TMAs ** Consultation and technical support in the construction and analyses of TMA * Research Pathology Services ** Macrodissection of tissue prior to isolation of DNA/RNA/protein to increase tumor purity ** Immunohistochemistry and In-situ hybridization ** Quantitative image analysis on conventional and TMA sections, including tissue scoring, Ki-67 labeling index, microvascular density counting, and tissue microarray scoring, etc. * Bio-molecular Assessment ** Cellular DNA, RNA and protein prepared by the Tissue Repository from banked specimens or any other biomolecules submitted by investigators can be qualitatively assessed by Agilent Bioanalyzer, prior to use for downstream applications such as microarray and/or qRT-PCR analysis

Proper citation: Hollings Cancer Center Tissue Biorepository and Research Pathology Services Shared Resource (RRID:SCR_004626) Copy   


  • RRID:SCR_008234

    This resource has 1+ mentions.

http://www.cs.ualberta.ca/~bioinfo/PA/GOSUB/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 30, 2015. Refer to Proteome Analyst 3.0. Subcellular Localization and GO General Molecular Function predictions for many model organism proteomes using Protein Analyst, with a very high coverage rate. When users blast their proteins against the database of results, they will not only be shown blast homologs from the model organisms, but also the Subcellular Localization and GO General Molecular Function predictions as well.

Proper citation: Proteome Analyst PA-GOSUB (RRID:SCR_008234) Copy   


http://www.ebi.ac.uk/Tools/blast2/index.html

It is used to compare a novel sequence with those contained in nucleotide and protein databases by aligning the novel sequence with previously characterized genes.

Proper citation: Washington University Basic Local Alignment Search Tool (RRID:SCR_008285) Copy   


  • RRID:SCR_008451

    This resource has 1+ mentions.

http://www.uwstructuralgenomics.org/

It is a specialized research center supported by the Protein Structure Initiative (PSI) of the National Institute of General Medical Sciences (NIGMS), one of the National Institutes of Health (NIH). PSI is a federal, university, and industry effort aimed at dramatically reducing the costs and lessening the time it takes to determine a three-dimensional protein structure. The long-range goal of PSI is to solve 10,000 protein structures in 10 years and to make the three-dimensional atomic-level structures of most proteins easily obtainable from knowledge of their corresponding DNA sequences. CESG is located within the Department of Biochemistry at the University of Wisconsin-Madison (Madison, WI) and the Department of Biochemistry at the Medical College of Wisconsin (Milwaukee, WI). CESG develops new methods and technologies to address unique eukaryotic bottlenecks and disseminates its methodologies and experimental results to the scientific community worldwide through: :- Cell-Free Protein Production Workshops :- Plasmids at PSI Materials Repository :- Posters Presented at Scientific Meetings :- Publications in PubMed / PubMed Central :- Sesame (LIMS) Available for Researchers :- Solved Structures in the Protein Data Bank :- Technology Dissemination Reports They have welcomed requests by researchers to solve eukaryotic protein structures, particularly medically relevant proteins, through our Online Structure Request System for Researchers. They have solved many community-nominated targets and deposited information about these targets in public databases and published on our investigations and findings. Sponsors: CESG is supported by NIH / NIGMS Protein Structure Initiative grant numbers U54 GM074901 and P50 GM064598.

Proper citation: CESG (RRID:SCR_008451) Copy   


https://www.proteinspire.org/MOPED/

An expanding multi-omics resource that enables rapid browsing of gene and protein expression information from publicly available studies on humans and model organisms. MOPED also serves the greater research community by enabling users to visualize their own expression data, compare it with existing studies, and share it with others via private accounts. MOPED uniquely provides gene and protein level expression data, meta-analysis capabilities and quantitative data from standardized analysis utilizing SPIRE (Systematic Protein Investigative Research Environment). Data can be queried for specific genes and proteins; browsed based on organism, tissue, localization and condition; and sorted by false discovery rate and expression. MOPED links to various gene, protein, and pathway databases, including GeneCards, Entrez, UniProt, KEGG and Reactome. The current version of MOPED (MOPED 2.5) The current version of MOPED (MOPED 2.5, 2014) contains approximately 5 million total records including ~260 experiments and ~390 conditions.

Proper citation: MOPED - Model Organism Protein Expression Database (RRID:SCR_006065) Copy   


  • RRID:SCR_004426

    This resource has 5000+ mentions.

http://www.uniprot.org/help/uniprotkb

Central repository for collection of functional information on proteins, with accurate and consistent annotation. In addition to capturing core data mandatory for each UniProtKB entry (mainly, the amino acid sequence, protein name or description, taxonomic data and citation information), as much annotation information as possible is added. This includes widely accepted biological ontologies, classifications and cross-references, and experimental and computational data. The UniProt Knowledgebase consists of two sections, UniProtKB/Swiss-Prot and UniProtKB/TrEMBL. UniProtKB/Swiss-Prot (reviewed) is a high quality manually annotated and non-redundant protein sequence database which brings together experimental results, computed features, and scientific conclusions. UniProtKB/TrEMBL (unreviewed) contains protein sequences associated with computationally generated annotation and large-scale functional characterization that await full manual annotation. Users may browse by taxonomy, keyword, gene ontology, enzyme class or pathway.

Proper citation: UniProtKB (RRID:SCR_004426) Copy   


http://www.emouseatlas.org/emage

A database of in situ gene expression data in the developing mouse embryo and an accompanying suite of tools to search and analyze the data. mRNA in situ hybridization, protein immunohistochemistry and transgenic reporter data is included. The data held is spatially annotated to a framework of 3D mouse embryo models produced by EMAP (e-Mouse Atlas Project). These spatial annotations allow users to query EMAGE by spatial pattern as well as by gene name, anatomy term or Gene Ontology (GO) term. The conceptual framework which houses the descriptions of the gene expression patterns in EMAGE is the EMAP Mouse Embryo Anatomy Atlas. This consists of a set of 3D virtual embryos at different stages of development, as well as an accompanying ontology of anatomical terms found at each stage. The raw data images can be conventional 2D photographs (of sections or wholemount specimens) or 3D images of wholemount specimens derived from Optical Projection Tomography (OPT) or confocal microscopy. Users may submit data using a Data submission tool or without.

Proper citation: EMAGE Gene Expression Database (RRID:SCR_005391) Copy   


  • RRID:SCR_008522

    This resource has 500+ mentions.

http://foldx.crg.es/

A computer algorithm that provides a fast and quantitative estimation of the importance of the interactions contributing to the stability of proteins and protein complexes. The predictive power of FOLDEF has been tested on a very large set of point mutants (1088 mutants) spanning most of the structural environments found in proteins . FoldX uses a full atomic description of the structure of the proteins. The different energy terms taken into account in FoldX have been weighted using empirical data obtained from protein engineering experiments.

Proper citation: FoldX (RRID:SCR_008522) Copy   


  • RRID:SCR_011819

    This resource has 500+ mentions.

http://www.ebi.ac.uk/Tools/sss/fasta/

Software package for DNA and protein sequence alignment to find regions of local or global similarity between Protein or DNA sequences, either by searching Protein or DNA databases, or by identifying local duplications within a sequence.

Proper citation: FASTA (RRID:SCR_011819) Copy   


http://coot.embl.de/g2d/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A database of candidate genes for mapped inherited human diseases. Candidate priorities are automatically established by a data mining algorithm that extracts putative genes in the chromosomal region where the disease is mapped, and evaluates their possible relation to the disease based on the phenotype of the disorder. Data analysis uses a scoring system developed for the possible functional relations of human genes to genetically inherited diseases that have been mapped onto chromosomal regions without assignment of a particular gene. Methodology can be divided in two parts: the association of genes to phenotypic features, and the identification of candidate genes on a chromosonal region by homology. This is an analysis of relations between phenotypic features and chemical objects, and from chemical objects to protein function terms, based on the whole MEDLINE and RefSeq databases.

Proper citation: Candidate Genes to Inherited Diseases (RRID:SCR_008190) Copy   


  • RRID:SCR_016133

    This resource has 10+ mentions.

https://github.com/soedinglab/hh-suite

Software package for sensitive protein sequence searching based on the pairwise alignment of hidden Markov models (HMMs). Used for sequence-based protein function and structure prediction what depends on sequence-search sensitivity and accuracy of the resulting sequence alignments.

Proper citation: HH-suite (RRID:SCR_016133) Copy   


  • RRID:SCR_016113

    This resource has 10+ mentions.

https://rostlab.org/node/960

Alignment software for large-scale protein contact or protein-protein interaction prediction optimized for speed through shorter runtimes. FreeContact provides the opportunity to compute contact predictions in any environment (desktop or cloud).

Proper citation: FreeContact (RRID:SCR_016113) Copy   


  • RRID:SCR_018187

    This resource has 100+ mentions.

https://www.thegpm.org/crap/

List of proteins commonly found in proteomics experiments that are present either by accident or through unavoidable contamination of protein samples. List is based on analysis of current version of GPMDB, as well as suggestions by users. Current version of cRAP in FASTA format can be obtained from the GPM FTP site.

Proper citation: cRAP protein sequences (RRID:SCR_018187) Copy   


  • RRID:SCR_017975

    This resource has 100+ mentions.

http://www.cbs.dtu.dk/services/NetPhos/

Web tool as artificial neural network method that predicts phosphorylation sites in independent sequences. Web application based on determination of activity of protein kinases using in vitro assays with either naturally occurring peptides or synthetic peptides. NetPhos 3.1 server predicts serine, threonine or tyrosine phosphorylation sites in eukaryotic proteins using ensembles of neural networks. Both generic and kinase specific predictions are performed. Generic predictions are identical to predictions performed by NetPhos 2.0. Kinase specific predictions are identical to predictions by NetPhosK 1.0. NetPhos 3.1 is available as stand-alone software package.

Proper citation: NetPhos (RRID:SCR_017975) Copy   


http://himc.stanford.edu

Core designed for immune monitoring services for clinical and translational studies. Goals include providing standardized, state-of-the art immune monitoring assays at RNA, protein, and cellular level, testing and developing new technologies for immune monitoring, archive, report, and mine data from immune monitoring studies. HIMC uses online database for integration of data from standard HIMC assays, along with de-identified clinical and demographic data.

Proper citation: Stanford University Human Immune Monitoring Center Core Facility (RRID:SCR_018266) Copy   


  • RRID:SCR_005729

    This resource has 10+ mentions.

http://hollow.sourceforge.net/

HOLLOW facilitates the production of surface images of proteins. HOLLOW is a portable command-line utility written in Python 2.4-2.7; it does not have any other dependencies (although running under the PyPy JIT interpreter, it runs much faster). The input is a PDB file. The output is a PDB file of dummy water atoms that forms a cast of the voids and channels of a protein. HOLLOW generates a surface from a cast of the protein surface. HOLLOW fills the interior spaces of a protein structure with dummy atoms defined on an overlapping grid. The surface generated by these dummy atoms can be shown to reproduce the surface of the protein at the ideal limit. The use of the surface of the dummy atoms allows us to focus on a specific piece of the interior surface. Simply by deleting dummy atoms, the interior surface can be trimmed to produce a custom portion of the interior space. For advanced coloring of the surface, the B-factor of the dummy atoms can be calculated as the average of the B-factor of the protein atoms surrounding the dummy atoms. This allows various colorings of the surface to be conveyed through the B-factor field of the PDB files. The volume filling representation facilitated by HOLLOW is meant to complement other programs that identify voids, pockets and channels, such as SPHGEN and CASTp, which identify binding sites but cannot produce output that can be rendered in standard molecular graphics software. HOLLOW can be used to help render these binding pockets.

Proper citation: HOLLOW (RRID:SCR_005729) Copy   



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