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| Resource Name | Proper Citation | Abbreviations | Resource Type |
Description |
Keywords | Resource Relationships | |||||||||||||
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SENTRA: a database of prokaryotic signal transduction proteins Resource Report Resource Website |
SENTRA: a database of prokaryotic signal transduction proteins (RRID:SCR_007922) | SENTRA | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A database of signal transduction proteins encoded in completely sequenced prokaryotic genomes. Sentra consists of two principal components, a manually curated list of signal transduction proteins in 202 completely sequenced prokaryotic genomes and an automatically generated listing of predicted signaling proteins in 235 sequenced genomes that are awaiting manual curation. In addition to two-component histidine kinases and response regulators, the database now lists manually curated Ser/Thr/Tyr protein kinases and protein phosphatases, as well as adenylate and diguanylate cyclases and c-di-GMP phosphodiesterases, as defined in several recent reviews. All entries in Sentra are extensively annotated with relevant information from public databases (e.g. UniProt, KEGG, PDB and NCBI). Sentra's infrastructure was redesigned to support interactive cross-genome comparisons of signal transduction capabilities of prokaryotic organisms from a taxonomic and phenotypic perspective and in the framework of signal transduction pathways from KEGG. Sentra leverages the PUMA2 system to support interactive analysis and annotation of signal transduction proteins by the users. | signal transduction, protein, microbial | has parent organization: Argonne National Laboratory | PMID:17135204 PMID:11752334 |
THIS RESOURCE IS NO LONGER IN SERVICE | SCR_007922 | 2026-07-28 09:41:56 | 0 | ||||||||
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Gene Atlas Resource Report Resource Website 10+ mentions |
Gene Atlas (RRID:SCR_008089) | Geneatlas | data or information resource, database, atlas | This website allows visitors to search for genes of interest based on their spatial expression patterns in the Postnatal Day 7 mouse brain. Geneatlas provides two searching tools: A graphical interface for customized spatial queries; A textual interface for querying annotated structures. Geneatlas is the product of a collaboration between researchers at Baylor College of Medicine, Rice University, and University of Houston. | gene, brain, mouse, protein, spatial expression, molecular neuroanatomy resource, FASEB list |
has parent organization: University of Houston; Texas; USA has parent organization: Baylor University; Texas; USA |
Burroughs Wellcome Fund ; NLM 5T15LM07093; NCRR P41RR02250 |
nif-0000-10987 | SCR_008089 | 2026-07-28 09:42:16 | 47 | ||||||||
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Metabolic Network Exchange Resource Report Resource Website 1+ mentions |
Metabolic Network Exchange (RRID:SCR_008124) | data or information resource, database | MetNet database contains information on networks of metabolic and regulatory and interactions in Arabidopsis. This information is based on input from biologists in their area of expertise. Types of interactions in MetNetDB include transcription, translation, protein modification, assembly, allosteric regulation, translocation from one subcellular compartment to another. Other fields describing the interactions are subcellular location, confidence, directionality, references, evidence, and synonyms. Data on entities (DNA, RNA, polypeptides, protein complexes, metabolites) are derived from web databases (gene related databases: TAIR, GO, MapMan/GabiPD; protein related databases: PPDB, AMPDB, AtNoPDB, AraPerox, PLprot, BRENDA; metabolite related databases: ChEBI, PubChem, KEGG, NCI compound library, NIST MS library), in some cases with additional annotation by experts. Network information from MetNetDB can be converted to an XML file by XML Builder. From this XML file, it can be transferred to exploRase, which uses the network in conjunction with statistical analysis of expression data; to Cytoscape/FCM, which finds cycles and pathways in the network, and visualizes and models it in combination with expression data; and to MetNetVR, where the network can be visualized in 3D. | allosteric regulation, arabidopsis, interaction, metabolic, protein, regulatory, subcellular, transcription, translation | has parent organization: Iowa State University; Iowa; USA | nif-0000-20871 | SCR_008124 | MetNetDB | 2026-07-28 09:42:17 | 1 | |||||||||
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Kinase Pathway Database Resource Report Resource Website 1+ mentions |
Kinase Pathway Database (RRID:SCR_008199) | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. KinasePathwayDatabase is an integrated database concerning completed sequenced major eukaryotes, which contains the classification of protein kinases and their functional conservation and orthologous tables among species, protein-protein interaction data, domain information, structural information, and automatic pathway graph image interface. The protein-protein interactions are extracted by natural language processing (NLP) from abstracts using basic word pattern and protein name dictionary GENA: developed by our group. In this system, pathways are easily compared among species using protein interactions data more than 47,000 and orthologous tables. | eukaryote, functional, automatic, classification, conservation, domain, interaction, intermolecular interactions and signaling pathways databases, kinase, orthologous, pathway, protein, sequence, specie, structural, image | has parent organization: University of Tokyo; Tokyo; Japan | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-21235 | SCR_008199 | Kinase Pathway Database | 2026-07-28 09:42:17 | 2 | ||||||||
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Peroxisome Database Resource Report Resource Website 10+ mentions |
Peroxisome Database (RRID:SCR_008352) | data or information resource, database | The aim of the PEROXISOME database (PeroxisomeDB) is to gather, organize and integrate curated information on peroxisomal genes, their encoded proteins, their molecular function and metabolic pathway they belong to, and their related disorders. PeroxisomeDB contains the complete peroxisomal proteome of Homo sapiens (encoded by 85 genes) and Saccharomyces cerevisiae (encoded by 61 genes). Now, we have included 34 new organism genomes with the acquisition of 2426 new peroxisomal homolog proteins. PeroxisomeDB 2.0 integrates the peroxisomal metabolome of whole microbody family by the new incorporation of the glycosome proteomes of trypanosomatids and the glyoxysome proteome of Arabidopsis thaliana. The site also provides a Peroxisome Metabolome of peroxisomal genes and proteins, their molecular interactions and metabolic pathways, tools for comparative genomics, predictive tools. Sponsors: Preoxisome Database is funded by Institut de Gntique et deBiologie Molculaire et Cellulaire. | family, function, gene, arabidopsis thaliana, disorder, genome, genomic, glycosome, glyoxysome, homolog, homo sapiens, interaction, metabolic, metabolome, microbody, molecular, organism, pathway, peroxisome, protein, proteome, saccharomyces cerevisiae, trypanosomatid | nif-0000-25216 | SCR_008352 | Preoxisomedb | 2026-07-28 09:42:08 | 27 | ||||||||||
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The Protein Coil Library Resource Report Resource Website 1+ mentions |
The Protein Coil Library (RRID:SCR_008233) | data or information resource, database | The Protein Coil Library is a library of protein structure fragments derived from the Protein Data Bank (PDB). The fragments in this library are those fragments in the PDB that cannot be classified as either alpha-helix or beta-strand. Three-dimensional structures as well as side-chain and backbone torsion angles are stored in the database. The Protein Coil Library allows rapid and comprehensive access to non-alpha-helix and non-beta-strand fragments contained in the Protein Data Bank (PDB). The library contains both sequence and structure information together with calculated torsion angles for both the backbone and side chains. Several search options are implemented, including a query function that uses output from popular PDB-culling servers directly. Additionally, several popular searches are stored and updated for immediate access. The library is a useful tool for exploring conformational propensities, turn motifs, and a recent model of the unfolded state. The library stores the complete torsion angle descriptions for the fragments as well as the three dimensional structures of the fragments themselves. The goal of extracting and pre-calculating this data is to allow for more straightforward investigation of peptide structure without the background of secondary structure elements. In addition to searching by PDB ID, it is possible to download a particular size class, perform a batch search of PDB/chain ID''s, or download precompiled lists of PDB ID''s of interest (PDB Select, etc.). For users interested in browsing the entire database at once or maintaining their own locally-updated copy of the library, FTP access instructions are also provided. The files stored in the coil library FTP site or returned after a batch search are organized heirarchically by PDB ID. This is done to reduce filesystem access times and fascilitate searches using the UNIX find utility. At the lowest directory level in the heirarchy, files are further sorted by fragment length. As a result, the number of files in a particular directory is generally less then 50, yielding relatively fast access on UNIX/Linux filesystems. The heirarchical organization is based on the middle two letters of the PDB ID. For example, hen egg lysozyme, which has a PDB ID of 1HEL, will be located in the directory h/he/. At the final level, fragments of varying sizes are stored in directories that correspond to their fragment length. Again, using lysozyme as an example, any seven-residue fragments, if they exist, will reside in the directory h/he/7/. Similarly, seven-residue fragments from 2HEX and 1HE0 will also be in this location. Sponsors: The Protein Coil Library is funded by Johns Hopkins University. | element, fragment, alpha helix, angle, backbone, beta, coil, lysozyme, peptide, protein, protein structure databases, secondary, sequence, side chain, strand, structure, torsion | has parent organization: Johns Hopkins University; Maryland; USA | nif-0000-21338 | SCR_008233 | The Coil Library | 2026-07-28 09:42:03 | 1 | |||||||||
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Structure modeling of 907 G protein coupled receptors in the human genome Resource Report Resource Website 1+ mentions |
Structure modeling of 907 G protein coupled receptors in the human genome (RRID:SCR_008351) | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 19,2019.Database of tertiary structural modeling results of threading assembly refinement (TASSER) method for all 907 G protein-coupled receptors (GPCRs) in human genome. All sequences were collected from GPCR database http://www.gpcr.org/7tm/ and http://www.expasy.org/cgi-bin/lists?7tmrlist.txt. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. G protein-coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha) root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness of the in silico models for GPCR functional analysis. Sponsors: GPCR is funded by the University at Buffalo, Buffalo, New York. | endogenous, extracellular, family, functional, gene, cellular, couple, genome, gpcr, g protein, helix, homology, human, membrane, model, modeling, orf, protein, receptor, response, signal, structural, structural model, structure, template, tertiary, topology, transduction, transmembrane | has parent organization: Georgia Institute of Technology; Georgia; USA | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-25215 | SCR_008351 | GPCR | 2026-07-28 09:42:05 | 3 | ||||||||
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Hybrid Pattern Library Resource Report Resource Website |
Hybrid Pattern Library (RRID:SCR_008193) | HyPaLib | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. It contains annotated structural elements characteristic for certain classes of structural and/or functional RNAs. These elements are described in a language specifically designed for this purpose. The language allows convenient specification of hybrid patterns, i.e. motifs consisting of sequence features and structural elements together with sequence similarity and thermodynamic constraints. A system that searches complex patterns (on nucleic-acid or protein level) in large biosequence-databases. As patterns, they allow hybrid patterns, which combine sequence similarity, structure similarity and arbitrary characteristics, like thermodynamic constraints. Applications are in the research of highly specific Protein/RNA-interactions or in the search of RNA-tertiary-structure-interactions. They developed a declarative pattern description language, which is implemented by known and new pattern-matching algorithms and an optimizing backtracking procedure. To achieve high efficiency when screening large data sets, the patterns are divided and queries are composed. The significance of patterns is estimated by a Monte-Carlo procedure. Complex results of queries are processed by a visualizing component. A library of biologically relevant patterns is developed and it is provided on the WWW together with the search-tool. The evaluation of the tool w.r.t. to the biosequence databases will in some cases mean to make laboratory-experiments, in order to check algorithmically developed functional hypothesis. Sponsors: This project is supported by a grant from the Deutsche Forschungsgemeinschaft. It is part of the special program on Computational Methods for the Analysis and Interpretation of large genomic data | element, functional, biologically, biosequence, characteristic, class, constraint, hybrid, interaction, nucleic acid, pattern, protein, rna, screening, structural, tertiary, thermodynamic | has parent organization: Bielefeld University; North Rhine-Westphalia; Germany | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-21208 | SCR_008193 | Hybrid Pattern Library | 2026-07-28 09:42:05 | 0 | |||||||
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Cytokine Family Database Resource Report Resource Website 1+ mentions |
Cytokine Family Database (RRID:SCR_008134) | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. A collection of cDNA, gene and protein records of cytokines deposited in public databases provides various information about the cytokine members of vertebrates in other databases including NCBI GenBank, Swiss-Prot, UniGene, TIGR (The Institute for Genomic Research) Gene Indices, Ensembl, Entrez Gene, Mouse Genome Informatics (MGI) and Rat Genome Database (RGD). It also provides orthologous relationship of cytokine members and includes novel members identified in the databases. | family, fish, gene, amphibian, bird, cdna, chemokine, cow, cytokine, genome, human, mammalian, mouse, oncogene, phylogenetic, protein, rat, receptor, reptile, virus |
is listed by: 3DVC has parent organization: Kumamoto University; Kumamoto; Japan |
Japan Society for the Promotion of Science | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-20948 | http://cytokine.medic.kumamoto-u.ac.jp/ | SCR_008134 | dbCFC | 2026-07-28 09:42:00 | 1 | ||||||
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Ancient conserved untranslated sequences Resource Report Resource Website |
Ancient conserved untranslated sequences (RRID:SCR_008130) | ACUTS | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, Documented on August 12, 2014. Database that identifies new regulatory elements in untranslated regions of protein-coding genes (5 prime flanks, 5 prime UTRs, introns, 3 prime UTRs and 3 prime flanks). The analyses is focused on genes from metazoan species (essentially vertebrates, insects and nematodes). Information on highly conserved regions (sequences, alignments, annotations, bibliographic references) are compiled. Currently 176 out of 326 detected highly conserved regions (HCRs) have been analyzed and incorporated in the database. You can also access the list of annotated conserved elements and the list of conserved elements that remain to be processed. Their approach is based on comparative sequence analysis, for the identification of phylogenetic footprints. | echinoderm, footprint, fragment, functional, gene, alignment, analysis, annotation, chordate, cis-element, coding, degradation, divergence, dna, dnase, highly conserved region, homologous, intron, metazoan, mrna, non-coding, nucleotide, phylogenetic, post-transcriptional, promoter, protein, region, regulatory, segment, sequence, structural, transcriptional repressor, translation, untranslated region | has parent organization: Claude Bernard University Lyon 1; Lyon; France | PMID:9204283 | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-20934 | SCR_008130 | 2026-07-28 09:42:17 | 0 | |||||||
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Protein Data Bank Bind Database Resource Report Resource Website 1+ mentions |
Protein Data Bank Bind Database (RRID:SCR_008224) | PDBBIND Database | data or information resource, database | A database of binding affinities for the protein-ligand complexes in the Protein Data Bank (PDB). The PDBbind database is a collection of the experimentally measured binding affinities exclusively for the protein-ligand complexes available in the Protein Data Bank (PDB). It thus provides a link between energetic and structural information of those complexes and may be of great value to various molecular recognition studies. This site was last updated in 2007. The updated version of the resource is maintained by the Shanghai Institute of Organic Chemistry (http://www.pdbbind.org.cn). | energetic, affinity, atom, bind, bond, ligand, model, molecular, molecule, protein, structural, type |
uses: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is used by: Drug Design Data Resource |
University of Michigan; Michigan; USA ; Office of the Vice President of Research |
nif-0000-21314 | SCR_008224 | Protein DataBank Bind Database | 2026-07-28 09:42:03 | 2 | |||||||
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Protein Data Bank Site Resource Report Resource Website 1+ mentions |
Protein Data Bank Site (RRID:SCR_008227) | PDBSITE | data or information resource, database | Protein Data Bank (PDB) contains data on the spatial protein structures and their biologically active sites (i.e., ligand binding regions, enzyme catalytic centers, regions subjected to biochemical modifications, etc.). However, neither of the well known systems searching PDB does not provide the user with possibility to make the queries related with the active sites. A database PDBSITE storing the data on biologically active sites contained in the PDB database has been developed. PDBSITE accumulates amino acid content, structure features calculated by spatial protein structures, and physicochemical properties of sites and their spatial surroundings. | enzyme, functional, active, activity, amino acid, binding, biochemical, biological, biologically, biology, biotechnology, catalytic, dna, heterocomplex, inorganic, interaction, ligand, medicine, modification, molecular, organic, pattern, physiochemical, post-translational, primary, protein, protein sequence motifs and active sites databases, residue, rna, site, spatial, specificity, structural, structure, tertiary |
uses: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) is used by: PASSer has parent organization: Siberian Branch of the Russian Academy of Sciences; Novosibirsk; Russia |
PMID:15608173 | nif-0000-21317 | SCR_008227 | 2026-07-28 09:42:03 | 1 | ||||||||
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Phylogenetic Clusters of Orthologous Groups Ranking Resource Report Resource Website 1+ mentions |
Phylogenetic Clusters of Orthologous Groups Ranking (RRID:SCR_008223) | data or information resource, database | THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 20,2019.The COG-database has become a powerful tool in the field of comparative genomics. The construction of this data-base is based on sequence homologies of proteins from different completely sequenced genomes. Highly homologous proteins are assigned to clusters of orthologous groups. The updated collection of orthologous protein sets for prokaryotes and eukaryotes is expected to be a useful platform for functional annotation of newly sequenced genomes, including those of complex eukaryotes, and genome-wide evolutionary studies. The availability of multiple, essentially complete genome sequences of prokaryotes and eukaryotes spurred both the demand and the opportunity for the construction of an evolutionary classification of genes from these genomes. Such a classification system based on orthologous relationships between genes appears to be a natural framework for comparative genomics and should facilitate both functional annotation of genomes and large-scale evolutionary studies. Here is a major update of the previously developed system for delineation of Clusters of Orthologous Groups of proteins (COGs) from the sequenced genomes of prokaryotes and unicellular eukaryotes and the construction of clusters of predicted orthologs for 7 eukaryotic genomes, which we named KOGs after eukaryotic orthologous groups. The COG collection currently consists of 138,458 proteins, which form 4873 COGs and comprise 75% of the 185,505 (predicted) proteins encoded in 66 genomes of unicellular organisms. The eukaryotic orthologous groups (KOGs) include proteins from 7 eukaryotic genomes: three animals (the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster and Homo sapiens), one plant, Arabidopsis thaliana, two fungi (Saccharomyces cerevisiae and Schizosaccharomyces pombe), and the intracellular microsporidian parasite Encephalitozoon cuniculi. The current KOG set consists of 4852 clusters of orthologs, which include 59,838 proteins, or approximately 54% of the analyzed eukaryotic 110,655 gene products. Compared to the coverage of the prokaryotic genomes with COGs, a considerably smaller fraction of eukaryotic genes could be included into the KOGs; addition of new eukaryotic genomes is expected to result in substantial increase in the coverage of eukaryotic genomes with KOGs. Examination of the phyletic patterns of KOGs reveals a conserved core represented in all analyzed species and consisting of approximately 20% of the KOG set. This conserved portion of the KOG set is much greater than the ubiquitous portion of the COG set (approximately 1% of the COGs). In part, this difference is probably due to the small number of included eukaryotic genomes, but it could also reflect the relative compactness of eukaryotes as a clade and the greater evolutionary stability of eukaryotic genomes. | elegans, encephalitozoon, eukaryote, evolutionary, fly, fruit, fungus, gene, general genomics databases, animal, arabidopsis, caenorhabditis, cerevisiae, classification, comparative, cuniculi, drosophila, genome, genomic, homo, homology, intracellular, melanogaster, microsporidian, nematode, organism, ortholog, orthologous, parasite, pattern, phyletic, phylogenetic, plant, pombe, prokaryote, protein, saccharomyces, sapiens, schizosaccharomyces, sequence, thaliana, tool, unicellular | has parent organization: National Institutes of Health | THIS RESOURCE IS NO LONGER IN SERVICE | nif-0000-21313 | SCR_008223 | PCOGR | 2026-07-28 09:42:18 | 3 | ||||||||
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LPDB: Ligand-Protein DataBase Resource Report Resource Website 1+ mentions |
LPDB: Ligand-Protein DataBase (RRID:SCR_008172) | data or information resource, database | The Ligand Protein Database is designed to allow the selection of complexes based on various properties of receptors and ligands for the design and parametrization of new scoring functions or to assess and improve existing ones. Moreover, for each complex, a continuum of ligand positions ranging from the crystallographic position to points on the surface of the protein receptor allows an assessment of the energetic behavior of particular scoring functions. Access to the database is password protected. To obtain access to the LPDB, complete a form, available online, have it signed by your research advisor, and fax the completed form back to the attention of Professor Charles L. Brooks III, (858) 784-8688. There is no fee for academic use of the LPDB. We are currently working out details for licensing to our colleagues in industry. Please contact Professor Brooks to obtain current information on access to the LPDB. | complexes, ligand, protein, receptors | has parent organization: University of Michigan; Ann Arbor; USA | nif-0000-21245 | SCR_008172 | LPDB | 2026-07-28 09:42:01 | 2 | |||||||||
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Information Hyperlinked Over Proteins Resource Report Resource Website 10+ mentions |
Information Hyperlinked Over Proteins (RRID:SCR_004829) | iHOP | data or information resource, service resource, database | Information system that provides a network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. It provides this network as a natural way of accessing millions of PubMed abstracts. By using genes and proteins as hyperlinks between sentences and abstracts, the information in PubMed can be converted into one navigable resource, bringing all advantages of the internet to scientific literature research. Moreover, this literature network can be superimposed on experimental interaction data (e.g., yeast-two hybrid data from Drosophila melanogaster and Caenorhabditis elegans) to make possible a simultaneous analysis of new and existing knowledge. The network contains half a million sentences and 30,000 different genes from humans, mice, D. melanogaster, C. elegans, zebrafish, Arabidopsis thaliana, yeast and Escherichia coli. | phenotype, gene, protein, interaction, pathology, physiology, gene network, network, literature, gene function, text-mining, bio.tools |
is listed by: OMICtools is listed by: Debian is listed by: bio.tools is related to: PubMed has parent organization: Autonomous University of Madrid; Madrid; Spain |
European Union IST-2001- 32688; European Union QLRT-2001-00015 |
PMID:15226743 | Creative Commons Attribution-NoDerivs License, Works v3 | biotools:ihop, nif-0000-00232, OMICS_01185 | https://bio.tools/ihop | SCR_004829 | iHOP - Information Hyperlinked over Proteins | 2026-07-28 09:41:05 | 24 | ||||
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UCL/UCLH Biobank for Studying Health and Disease Resource Report Resource Website |
UCL/UCLH Biobank for Studying Health and Disease (RRID:SCR_004610) | UCL Biobank for studying Health and Disease | tissue bank, biomaterial supply resource, material resource | The UCL/UCLH Biobank for Studying Health and Disease has been primarily established to support the Research Programme and scientific needs, of the Pathology Department UCLH & the UCL Cancer Institute. The establishment of the core programme enables a centralised approach to the management and integration of all research groups working within these institutions, providing appropriate structure and support. The biobank has policies and guidelines to guarantee compliance with HTA legislation and to ensure quality standards will be maintained. The biobank stores normal and pathological specimens, surplus to diagnostic requirements, from relevant tissues and bodily fluids, as well as human tissue used in xenograft experiments. Stored tissues include; snap-frozen or cryopreserved tissue, formalin-fixed tissue, paraffin-embedded tissues, and slides prepared for histological examination. Tissues include resection specimens obtained surgically or by needle core biopsy. Bodily fluids include; whole blood, serum, plasma, urine, cerebrospinal fluid, milk, saliva and buccal smears and cytological specimens such as sputum and cervical smears. Fine needle aspirates obtained from tissues and bodily cavities (eg. pleura and peritoneum) are also collected. Where appropriate the biobank also stores separated cells, protein, DNA and RNA isolated from collected tissues and bodily fluids described above. Some of the tissue and aspirated samples are stored in the diagnostic archive. | specimen, pathology, tissue, bodily fluid, human tissue, xenograft, tissue, blood, serum, plasma, urine, cerebral spinal fluid, milk, saliva, buccal smear, sputum, cervical smear, pleura, peritoneum, cell, protein, dna, rna, snap-frozen, cryopreserved, formalin-fixed, paraffin-embedded, slide, normal, disease, cancer, frozen |
is listed by: One Mind Biospecimen Bank Listing has parent organization: University College London; London; United Kingdom |
Normal, Disease, Cancer | Private / Partners: The aim is to support primarily, Research in the Pathology Department, UCLH and the UCL-Cancer Institute but it will also support other UCLH partners. | nlx_143838 | SCR_004610 | UCL/UCLH Biobank for Studying Health Disease, UCL Biobank for studying Health Disease, UCL / UCLH Biobank for Studying Health Disease | 2026-07-28 09:41:05 | 0 | ||||||
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Pain Genes database Resource Report Resource Website 10+ mentions |
Pain Genes database (RRID:SCR_004771) | PainGenesdb | data or information resource, database | Database of genes regulated by pain derived from published manuscripts describing results of pain-relevant knockout studies. The database has two levels of exploration: across-gene and within-gene. The across-gene level, the PainGenesdbSelector, is encountered first. All genes in the database can be accessed and sorted by their gene name, protein name, common names and acronyms, or genomic position (by navigating a graphic representation of the mouse genome). The gene and protein names can be selected from an alphabetical list, or by typing a text string into a search box. | knock out mouse, pain sensation, mice, mutant, knockout, gene, genome, protein | has parent organization: McGill University; Montreal; Canada | Pain | Louise Edwards Foundation | PMID:17574758 | nlx_77039, r3d100012129 | https://doi.org/10.17616/R3WP95 | SCR_004771 | PainGenes DB | 2026-07-28 09:41:04 | 15 | ||||
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Apo and Holo structures DataBase Resource Report Resource Website 1+ mentions |
Apo and Holo structures DataBase (RRID:SCR_004800) | AH-DB | data or information resource, database | Database of apo and holo structure pairs of proteins before and after binding. Various protein functions have been shown directly associated with conformational transitions triggered by binding other molecules. Tertiary structures determined in the unbound and bound state are usually named apo and holo structures, respectively. AH-DB is the largest database of apo-holo structure pairs and provides a sophisticated interface to search and view the collected data. It contains 746314 apo-holo pairs of 3638 proteins from 702 organisms. | ah-db, ahdb, apo, holo, protein interaction, structural change, protein, protein structure, protein binding, bio.tools |
is listed by: Debian is listed by: bio.tools has parent organization: National Cheng Kung University; Tainan; Taiwan |
National Science Council Taiwan NSC 99-2628-E-006-017 | PMID:22084200 | The community can contribute to this resource | biotools:ah-db, nlx_143908 | https://bio.tools/ah-db | SCR_004800 | Apo-Holo DataBase | 2026-07-28 09:41:05 | 1 | ||||
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footprintDB Resource Report Resource Website 1+ mentions |
footprintDB (RRID:SCR_005368) | footprintDB | data or information resource, database | Database with 2797 unique DNA-binding proteins (mostly transcription factors, TFs), 4196 Position Weight Matrices (PWMs) and 13161 DNA Binding Sites extracted from the literature and other repositories. The binding interfaces of (most) proteins in the database are inferred from the collection of protein-DNA complexes described in 3D-footprint. The database predicts transcription factors which bind a specific DNA site or motif and DNA motifs or sites likely to be recognized by a specific DNA-binding protein. | transcription factor, dna motif, dna, motif, dna-binding protein, position weight matrix, protein |
is listed by: OMICtools has parent organization: Spanish National Research Council; Madrid; Spain |
Free | OMICS_00535 | SCR_005368 | 2026-07-28 09:41:21 | 9 | ||||||||
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PIE the search Resource Report Resource Website 1+ mentions |
PIE the search (RRID:SCR_005296) | PIE | data or information resource, service resource, database | A web service to extract Protein-protein interaction (PPI)-relevant articles from MEDLINE that provides protein interaction information (PPI) articles for biologists, baseline system performance for bio-text mining researchers and a compact PubMed-search environment for PubMed users. It accepts PubMed input formats including All Fields, Author, Journal, MeSH Terms, Publication Date, Title, and Title/Abstract with Boolean operations (AND, OR, and NOT). However, the output is the list of articles prioritized by PPI confidence rates. Some words (mostly gene/protein names) which contributed for PPI prediction are underlined and linked to Entrez or Entrez Gene. Even though our system focuses on a PubMed search environment, it also provides a CGI access for bio-text mining researchers. Using the CGI program, a list of PubMed IDs can be obtained as a query result, thus it can be utilized as a baseline system performance. PIE the search is based on a winning approach in the BioCreative III ACT competition (BC3)1. For input queries, MEDLINE articles are first retrieved through the PubMed service. PPI scores are calculated for the retrieved articles, and the articles are re-ranked based on scores. To effectively capture PPI patterns from biomedical literature, their approach utilizes both word and syntactic features for machine learning classifiers. Dependency parsing, gene mention tagging, and term-based features are utilized along with a Huber classifier. | protein interaction, protein-protein interaction, protein, interaction |
is listed by: OMICtools is related to: PubMed is related to: MEDLINE has parent organization: NCBI |
PMID:22199390 PMID:22151252 |
OMICS_01191 | SCR_005296 | Protein Interaction information Extraction the search | 2026-07-28 09:41:12 | 1 |
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