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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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://expasy.org/

Portal which provides access to scientific databases and software tools (i.e., resources) in different areas of life sciences including proteomics, genomics, phylogeny, systems biology, population genetics, transcriptomics etc. It contains resources from many different SIB groups as well as external institutions.

Proper citation: ExPASy Bioinformatics Resource Portal (RRID:SCR_012880) Copy   

•   Source: SciCrunch Registry

http://www.dpidb.genebee.msu.ru/

The database NPIDB (Nucleic acid Protein Interaction DataBase) contains information derived from structures of DNA-protein and RNA-protein complexes extracted from Protein Data Bank (PDB) (1932 complexes in the end of 2007). It is equipped with a web-interface and a set of tools for extracting biologically meaningful characteristics of complexes. They are committed to satisfy all potential database users in order to: 1. Provide an essential information on structural features of DNA-protein and RNA-protein interaction for the users who need to get acquainted with the problem. 2. Give an effective access to the reasonably structured information about all DNA-protein and RNA-protein complexes containing in PDB. 3. Allow all visitors a quick access to our own research.

Proper citation: DNA-Protein Interaction Database (RRID:SCR_000754) Copy   

•   Source: SciCrunch Registry

http://www.ampdb.bcs.uwa.edu.au/

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on September 23,2022. The Arabidopsis Mitochondrial Protein Database is an Internet-accessible relational database containing information on the predicted and experimentally confirmed protein complement of mitochondria from the model plant Arabidopsis thaliana. This database, and the proteomic data contained in it for Arabidopsis mitochondria, have been accepted for publication in The Plant Cell.

Proper citation: AMPDB: Arabidopsis Mitochondrial Protein Database (RRID:SCR_000758) Copy   

•   Source: SciCrunch Registry

http://www.biorag.org/index.php

Bio Resource for array genes is a free online resource for easy access to collective and integrated information from various public biological resources for human, mouse, rat, fly and c. elegans genes. The resource includes information about the genes that are represented in Unigene clusters. This resource provides interactive tools to selectively view, analyze and interpret gene expression patterns against the background of gene and protein functional information. Different query options are provided to mine the biological relationships represented in the underlying database. Search button will take you to the list of query tools available. This Bio resource is a platform designed as an online resource to assist researchers in analyzing results of microarray experiments and developing a biological interpretation of the results. This site is mainly to interpret the unique gene expression patterns found as biological changes that can lead to new diagnostic procedures and drug targets. This interactive site allows users to selectively view a variety of information about gene functions that is stored in an underlying database. Although there are other online resources that provide a comprehensive annotation and summary of genes, this resource differs from these by further enabling researchers to mine biological relationships amongst the genes captured in the database using new query tools. Thus providing a unique way of interpreting the microarray data results based on the knowledge provided for the cellular roles of genes and proteins. A total of six different query tools are provided and each offer different search features, analysis options and different forms of display and visualization of data. The data is collected in relational database from public resources: Unigene, Locus link, OMIM, NCBI dbEST, protein domains from NCBI CDD, Gene Ontology, Pathways (Kegg, Genmapp and Biocarta) and BIND (Protein interactions). Data is dynamically collected and compiled twice a week from public databases. Search options offer capability to organize and cluster genes based on their Interactions in biological pathways, their association with Gene Ontology terms, Tissue/organ specific expression or any other user-chosen functional grouping of genes. A color coding scheme is used to highlight differential gene expression patterns against a background of gene functional information. Concept hierarchies (Anatomy and Diseases) of MESH (Medical Subject Heading) terms are used to organize and display the data related to Tissue specific expression and Diseases. Sponsors: BioRag database is maintained by the Bioinformatics group at Arizona Cancer Center. The material presented here is compiled from different public databases. BioRag is hosted by the Biotechnology Computing Facility of the University of Arizona. 2002,2003 University of Arizona.

Proper citation: Bio Resource for Array Genes Database (RRID:SCR_000748) Copy   

•   Source: SciCrunch Registry

http://www.molecularconnections.com/home/en/home/products/netPro

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1, 2023. Comprehensive database of Protein-Protein and Protein-Small molecules interaction, consisting of more than 320,000 interactions captured from more than 1500 abstracts, approximately 1600 published journals and more than 60,000 references. The strength of NetPro lies in the complete manual curation of literature. It covers several entities other than proteins as interacting partners, like RNA, DNA, processes, etc. with well defined, exhaustive interaction terms. NetPro has received several accolades for the quality and quantity of data it contains. It has become an important resource for target identification, validation and pathway research and has subscribers from all over the globe including 3 of the top 5 pharmas.

Proper citation: Molecular Connections NetPro (RRID:SCR_000395) Copy   

•   Source: SciCrunch Registry

http://psychiatry.igm.jhmi.edu/SynaptomeDB/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Ontology-based knowledgebase for synaptic genes. These genes encode components of the synapse including neurotransmitters and their receptors, adhesion / cytoskeletal proteins, scaffold proteins, transporters, and others. It integrates various and complex data sources for synaptic genes and proteins., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SynaptomeDB (RRID:SCR_000157) Copy   

•   Source: SciCrunch Registry

http://www.bindingdb.org

Web accessible database of data extracted from scientific literature, focusing on proteins that are drug-targets or candidate drug-targets and for which structural data are present in Protein Data Bank . Website supports query types including searches by chemical structure, substructure and similarity, protein sequence, ligand and protein names, affinity ranges and molecular weight . Data sets generated by BindingDB queries can be downloaded in form of annotated SDfiles for further analysis, or used as basis for virtual screening of compound database uploaded by user. Data are linked to structural data in PDB via PDB IDs and chemical and sequence searches, and to literature in PubMed via PubMed IDs .

Proper citation: BindingDB (RRID:SCR_000390) Copy   

•   Source: SciCrunch Registry

http://webclu.bio.wzw.tum.de/dima/

DIMA, the Domain Interaction Map, aims at becoming a comprehensive resource for functional and physical interactions among conserved protein-domains. The scope of the resource comprises both experimental data and computational predictions. Several methods and datasets have been integrated, already and inclusion of others is under way.

Proper citation: Domain Interaction MAp (RRID:SCR_000731) Copy   

•   Source: SciCrunch Registry

http://text0.mib.man.ac.uk/software/mldic/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 9, 2022. System that retrieves relevant UniProt IDs from BioThesaurus entries using a soft string matching algorithm.

Proper citation: Smart Dictionary Lookup (RRID:SCR_000568) Copy   

•   Source: SciCrunch Registry

http://aclame.ulb.ac.be/

A database dedicated to the collection and classification of mobile genetic elements (MGEs) from various sources, comprising all known phage genomes, plasmids and transposons. In addition to provide information on the full genomes and genetic entities, it aims at building a comprehensive classification of the functional modules of MGE's at the protein, gene, and higher levels. Prophinder, a tool dedicated to the detection of prophages in sequenced bacterial genomes, is available on ACLAME.

Proper citation: A Classification of Mobile genetic Elements (RRID:SCR_001694) Copy   

•   Source: SciCrunch Registry

http://web.expasy.org/glycomod/

A tool that can predict the possible oligosaccharide structures that occur on proteins from their experimentally determined masses. This is done by comparing the mass of the glycan to a list of pre-computed masses of glycan compositions. The program can be used with free or derivatised glycans and for glycopeptides where the peptide mass or protein is known. Compositional constraints can be applied to the output. Note: You can use GlycanMass to calculate the mass of an oligosaccharide structure from its oligosaccharide composition.

Proper citation: GlycoMod (RRID:SCR_001602) Copy   

•   Source: SciCrunch Registry

http://www.glycosciences.de/modeling/glyprot/

Web-based tool that enables meaningful N-glycan conformations to be attached to all the spatially accessible potential N-glycosylation sites of a known three-dimensional (3D) protein structure. The 3D structure of protein is required as input. Potential N-glysylations site are automatically detected. The attached glycan are constructed with SWEET-II, http://www.glycosciences.de/modeling/sweet2/doc/index.php

Proper citation: GlyProt (RRID:SCR_001560) Copy   

•   Source: SciCrunch Registry

http://mitominer.mrc-mbu.cam.ac.uk/

A database of mitochondrial proteomics data. It includes two sets of proteins: the MitoMiner Reference Set, which has 10477 proteins from 12 species; and MitoCarta, which has 2909 proteins from mouse and human mitochondrial proteins. MitoMiner provides annotation from the Gene Ontology (GO) and UniProt databases. This reference set contains all proteins that are annotated by either of these resources as mitochondrial in any of the species included in MitoMiner. MitoMiner data via is available via Application Programming Interface (API). The client libraries are provided in Perl, Python, Ruby and Java.

Proper citation: MitoMiner (RRID:SCR_001368) Copy   

•   Source: SciCrunch Registry

https://mendel.imp.ac.at/gpi/gpi_server.html

Prediction tool locating potential GPI-modification sites in precursor sequences applied for large-scale protein sequence database searches. The composite prediction function (with separate parametrization for metazoan and protozoan proteins) consists of terms evaluating both amino acid type preferences at sequence positions near a supposed omega-site as well as the concordance with general physical properties encoded in multi-residue correlation within the motif sequence. The latter terms are especially successful in rejecting non-appropriate sequences from consideration. The algorithm has been validated with a self-consistency and two jack-knife tests for the learning set of fully annotated sequences from the SWISS-PROT database as well as with a newly created database big-Pi (more than 300 GPI-motif mutations extracted from original literature sources). The accuracy of predicting the effect of mutations in the GPI sequence motif was above 83 %.

Proper citation: big-PI Predictor (RRID:SCR_001599) Copy   

•   Source: SciCrunch Registry

http://mips.helmholtz-muenchen.de/genre/proj/corum

Database of manually annotated protein complexes from mammalian organisms. Annotation includes protein complex function, localization, subunit composition, literature references and more. All information is obtained from individual experiments published in scientific articles, but data from high-throughput experiments is excluded.
The majority of protein complexes in CORUM originates from man (65%), followed by mouse (14%) and rat (14%)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CORUM (RRID:SCR_002254) Copy   

•   Source: SciCrunch Registry