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SYSTERS is a database of protein sequences grouped into homologous families and superfamilies. The SYSTERS project aims to provide a meaningful partitioning of the whole protein sequence space by a fully automatic procedure. A refined two-step algorithm assigns each protein to a family and a superfamily. The sequence data underlying SYSTERS release 4 now comprise several protein sequence databases derived from completely sequenced genomes (ENSEMBL, TAIR, SGD and GeneDB), in addition to the comprehensive Swiss-Prot/TrEMBL databases. To augment the automatically derived results, information from external databases like Pfam and Gene Ontology are added to the web server. Furthermore, users can retrieve pre-processed analyses of families like multiple alignments and phylogenetic trees. New query options comprise a batch retrieval tool for functional inference about families based on automatic keyword extraction from sequence annotations. A new access point, PhyloMatrix, allows the retrieval of phylogenetic profiles of SYSTERS families across organisms with completely sequenced genomes. Gene, Human, Vertebrate, Genome, Human ORFs
Proper citation: SYSTERS (RRID:SCR_007955) Copy
http://supfam.org/SUPERFAMILY/
SUPERFAMILY is a database of structural and functional protein annotations for all completely sequenced organisms. The SUPERFAMILY annotation is based on a collection of hidden Markov models, which represent structural protein domains at the SCOP superfamily level. A superfamily groups together domains which have an evolutionary relationship. The annotation is produced by scanning protein sequences from over 1,700 completely sequenced genomes against the hidden Markov models.
Proper citation: SUPERFAMILY (RRID:SCR_007952) Copy
Database to explore known and predicted interactions of chemicals and proteins. It integrates information about interactions from metabolic pathways, crystal structures, binding experiments and drug-target relationships. Inferred information from phenotypic effects, text mining and chemical structure similarity is used to predict relations between chemicals. STITCH further allows exploring the network of chemical relations, also in the context of associated binding proteins. Each proposed interaction can be traced back to the original data sources. The database contains interaction information for over 68,000 different chemicals, including 2200 drugs, and connects them to 1.5 million genes across 373 genomes and their interactions contained in the STRING database.
Proper citation: Search Tool for Interactions of Chemicals (RRID:SCR_007947) Copy
Collection of transmembrane protein datasets containing experimentally derived topology information from the literature and from public databases. Web interface of TOPDB includes tools for searching, relational querying and data browsing, visualisation tools for topology data.
Proper citation: Topology Data Bank of Transmembrane Proteins (RRID:SCR_007964) Copy
It provides a database based on a pre-computed similarity matrix covering the similarity space formed by >4 million amino acid sequences from public databases and completely sequenced genomes. The database is capable of handling very large datasets and is updated incrementally. For sequence similarity searches and pairwise alignments, we implemented a grid-enabled software system, which is based on FASTA heuristics and the Smith Waterman algorithm. SimpleSIMAP and AdvancedSIMAP retrieve homologs for given protein sequences that need to be contained in the SIMAP database. While SimpleSIMAP provides only selected parameters and preconfigured search spaces, the AdvancedSIMAP allows the user to specify search space, filtering and sorting parameters in a flexible manner. Both types of queries result in lists of homologs that are linked in turn to their homologs. So the web interfaces allow users to explore quickly and interactively the protein world by homology. Sponsors: SIMAP is supported by the Department of Genome Oriented Bioinformatics of the Technische Universitt Mnchen and the Institute for Bioinformatics of the GSF-National Research Center for Environment and Health.
Proper citation: SIMAP (RRID:SCR_007927) Copy
http://www.grt.kyushu-u.ac.jp/spad/
It is divided to four categories based on extracellular signal molecules (Growth factor, Cytokine, and Hormone) and stress, that initiate the intracellular signaling pathway. SPAD is compiled in order to describe information on interaction between protein and protein, protein and DNA as well as information on sequences of DNA and proteins. There are multiple signal transduction pathways: cascade of information from plasma membrane to nucleus in response to an extracellular stimulus in living organisms. Extracellular signal molecule binds specific intracellular receptor, and initiates the signaling pathway. Now, there is a large amount of information about the signaling pathway which controls the gene expression and cellular proliferation. We have developed an integrated database SPAD to understand the overview of signaling transduction.
Proper citation: Signaling Pathway Database (RRID:SCR_008243) Copy
http://escience.invitrogen.com/ipath/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. LINNEA Pathways is a user-friendly comprehensive online resource for gene- or protein-based scientific research. It is based on a total of 248 signaling and metabolic human biological pathway maps created for Invitrogen by GeneGo. The current version of iPath features 225 maps displaying human regulatory and metabolic pathways established in experimental literature produced by MetaCore from GeneGo, Inc. The map objects (proteins, genes, EC functions, and compounds) are connected via metabolic transformations and physical protein interactions, which were assembled by the GeneGo team of experienced annotators, geneticists, and biochemists. The pathways are organized in a vertical fashion following the general signaling path from signaling molecules and membrane receptors, via signal transduction cascades, to transcription factors and their gene targets. Following the natural organization of cellular machinery with highly interconnected pathways and modules, many maps are linked together via hyperlinked box symbols. Such linkage allows the reconstruction of a big picture view of human cell biology., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Invitrogen iPath (RRID:SCR_008120) Copy
ITFP is an integrated transcription factor (TF) platform, which included abundant TFs and targets message of mammalian. Support vector machine (SVM) algorithm combined with error-correcting output coding (ECOC) algorithm was utilized to identify and classify transcription factor from protein sequence of Human, Mouse and Rat. For transcription factor targets, a reverse engineering method named ARACNE was used to derive potential interaction pairs between transcription factor and downstream regulated gene from Human, Mouse and Rat gene expression profile data. Detailed information of gene expression profile data can be found in help page. Moreover, all data provided by the platform is free for non-commercial users and can be downloaded through links on help page.
Proper citation: Intergrated Transcription Factor Platform (RRID:SCR_008119) Copy
iRefWeb is an interface to a relational database containing the latest build of the interaction Reference Index (iRefIndex) which integrates protein interaction data from nine different interaction databases: BioGRID, BIND, CORUM, DIP, HPRD, INTACT, MINT, MPPI, MPACT and OPHID. Integration is achieved through a rigorously documented procedure for mapping protein IDs across databases, enabling systematic backtracking of the links used to establish the identity of the interaction partners. The iRefWeb interface groups interaction records from the different databases into a single non-redundant view. In particular iRefWeb facilitates comparing interaction records as seen by the various source databases relative to the PubMeds they were annotated from. iRefWeb is one of several views of the iRefIndex resource. Data are also available in a tab-delimited plain-text format (PSI-MITAB) as well as planned releases of a PSI-XML formatted version and a Cytoscape plugin. Further details about the iRefIndex project as well as data downloads are available from here . The method used to build iRefIndex is described in a recent publication.
Proper citation: Interaction Reference Index Web Interface (RRID:SCR_008118) Copy
A horizontally and vertically structured database that pulls scientific and medical information and describes it consistently using the Ingenuity Ontology. The Knowledge Base pulls information from journals, public molecular content databases, and textbooks. Data is curated and and integrated into the Knowledge Base .
Proper citation: Ingenuity Pathways Knowledge Base (RRID:SCR_008117) Copy
http://www.ebi.ac.uk/ipd/mhc/bola/
This website is intended to be the definitive source of information on the bovine major histocompatibility complex - its genes, proteins and polymorphism. Its purpose is to collate data on the Bovine Leucocyte Antigens (BoLA) and provide a forum for the analysis and nomenclature of polymorphisms in the genes and proteins of the bovine MHC. The BoLA nomenclature committee is a standing committee of the International Society for Animal Genetics. Its purpose is to collate data on the Bovine Leucocyte Antigens (BoLA) and provide a forum for the analysis and nomenclature of polymorphisms in the genes and proteins of the bovine MHC. The information gathered here is based on the BoLA workshop reports, which are published in Animal Genetics and the European Journal of Immunogenetics. The workshop report data are reproduced with the permission of the publishers Blackwell Science, and other text on the site is used with the permission of CRC Press.
Proper citation: BoLA Nomenclature: International Society for Animal Genetics (RRID:SCR_008142) Copy
The MIPS mammalian protein-protein interaction database (MPPI) is a new resource of high-quality experimental protein interaction data in mammals. The content is based on published experimental evidence that has been processed by human expert curators. It is a collection of manually curated high-quality PPI data collected from the scientific literature by expert curators. We took great care to include only data from individually performed experiments since they usually provide the most reliable evidence for physical interactions. To suit different users needs we provide a variety of interfaces to search the database: -Expert interface Simple but powerful boolean query language. -PPI search form Easy to use PPI search -Protein search Just find proteins of interest in the database Sponsors: This work is funded by a grant from the German Federal Ministry of Education and Research.
Proper citation: MIPS Mammalian Protein-Protein Interaction Database (RRID:SCR_008207) Copy
http://mips.helmholtz-muenchen.de/genre/proj/mpcdb/
A database of manually annotated mammalian protein complexes. To obtain a high-quality dataset, information was extracted from individual experiments described in the scientific literature. Data from high-throughput experiments was not included.
Proper citation: Mammalian Protein Complex Data Base (RRID:SCR_008209) Copy
http://locustdb.genomics.org.cn/
The migratory locust (Locusta migratoria) is an orthopteran pest and a representative member of hemimetabolous insects. Its transcriptomic data provide invaluable information for molecular entomology study of the insect and pave a way for comparative studies of other medically, agronomically, and ecologically relevant insects. This first transcriptomic database of the locust (LocustDB) has been developed, building necessary infrastructures to integrate, organize, and retrieve data that are either currently available or to be acquired in the future. It currently hosts 45,474 high quality EST sequences from the locust, which were assembled into 12,161 unigenes. This database contains original sequence data, including homologous/orthologous sequences, functional annotations, pathway analysis, and codon usage, based on conserved orthologous groups (COG), gene ontology (GO), protein domain (InterPro), and functional pathways (KEGG). It also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. LocustDB also provides information from comparative analysis based on data from the migratory locust and five other invertebrate species, such as the silkworm, the honeybee, the fruitfly, the mosquito and the nematode. It starts with the first transcriptome information for an orthopteran and hemimetabolous insect and will be extended to provide a framework for incorporation of in-coming genomic data of relevant insect groups and a workbench for cross-species comparative studies.
Proper citation: Migratory Locust EST Database (RRID:SCR_008201) Copy
http://www.ebi.ac.uk/asd/altsplice/index.html
AltSplice is a computer generated high quality data set of human transcript-confirmed splice patterns, alternative splice events, and the associated annotations. This data is being integrated with other data that is generated by other members of the ASD consortium. The ASD project will provide the following in its three year duration: -human curated database of alternative spliced genes and their properties -a computer generated database of alternatively spliced genes and their properties -the integration of the above and newly found knowledge in a user-friendly interface and research workbench for both bioinformaticists and biologists -DNA chips that are based on the data in the above databases -the DNA chips will be used to test against predisposition for and diagnoses of human diseases ASD aims to analyse this mechanism on a genome-wide scale by creating a database that contains all alternatively spliced exons from human, and other model species. Disease causing mutations seem to induce aberrations in the process of splicing and its regulation. The ASD consortium will develop a DNA microarray (chip) that contains cDNAs of all the splicing regulatory proteins and their isoforms, as well as a chip that contains a number of disease relevant genes. We will concentrate on three models of disease (breast cancer, FTDP-17, male infertility) in which a connection between mis-splicing and a pathological state has been observed. Finally, these chips will be developed as demonstrative kits to detect predisposition for and diagnosis of such diseases. Categories: Nucleotide Sequences: Gene Structure, Introns and Exons, & Splice Sites Databases
Proper citation: AltSplice Database of Alternative Spliced Events (RRID:SCR_008162) Copy
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. Doodle is a database that was developed to store and distribute information about the protein oligomerization domains that are encoded by various genomes. The protein oligomerization domains described here were found using the lambda repressor fusion system. Doodle uses a schema that is based on EnsEMBL, while also utilizing bioperl modules to both store and retrieve data. The frontend was developed entirely in perl, while the backend utilizes MySQL. GMOD was used to develop the genomic view.
Proper citation: Database of oligomerization domains from lambda experiments (RRID:SCR_008107) Copy
http://www.schematikon.org/Nh3D.html
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. It is freely available as a reference dataset for the statistical analysis of sequence and structure features of proteins in the PDB. It is a dataset of structurally dissimilar proteins. This dataset has been compiled by selecting well resolved representatives from the Topology level of the CATH database which hierarchically classifies all protein structures. These have been been pruned to remove: i) domains that may contain homologous elements (by pairwise sequence comparison and structural superposition of aligned residues) ii) internal duplications (by repeat detection) iii) regions with high B-Factor The statistical analysis of protein structures requires datasets in which structural features can be considered independently distributed, i.e. not related through common ancestry, and that fulfill minimal requirements regarding the experimental quality of the structures it contains. However, non-redundant datasets based on sequence similarity invariably contain distantly related homologues. Here a reference dataset of non-homologous protein domains is provided, assuming that structural dissimilarity at the topology level is incompatible with recognizable common ancestry. It contains the best refined representatives of each Topology level, validates structural dissimilarity and removes internally duplicated fragments. The compilation of Nh3D is fully scripted. The current Nh3D list contains 570 domains with a total of 90780 residues. It covers more than 70% of folds at the Topology level of the CATH database and represents more than 90% of the structures in the PDB that have been classified by CATH. Even though all protein pairs are structurally dissimilar, some pairwise sequence identities after global alignment are greater than 30%. Nh3D is freely available as a reference dataset for the statistical analysis of sequence and structure features of proteins in the PDB.
Proper citation: Nh3D: A Reference Dataset of Structures of Non-homologous Proteins (RRID:SCR_008212) Copy
http://jbirc.jbic.or.jp/hinv/ppi/
The PPI view displays H-InvDB human protein-protein interaction (PPI) information. It is constructed by assigning interaction data to H-InvDB proteins which were originally predicted from transcriptional products generated by the H-Invitational project. The PPI view is now providing 32,198 human PPIs comprised of 9,268 H-InvDB proteins. H-Invitational Database (H-InvDB) is an integrated database of human genes and transcripts. By extensive analyses of all human transcripts, we provide curated annotations of human genes and transcripts that include gene structures, alternative splicing isoforms, non-coding functional RNAs, protein functions, functional domains, sub-cellular localizations, metabolic pathways, protein 3D structure, genetic polymorphisms (SNPs, indels and microsatellite repeats) , relation with diseases, gene expression profiling, molecular evolutionary features, protein-protein interactions (PPIs) and gene families/groups. Sponsors: This research is financially supported by the Ministry of Economy, Trade and Industry of Japan (METI), the Ministry of Education, Culture, Sports, Science and Technology of Japan (MEXT) and the Japan Biological Informatics Consortium (JBIC). Also, this work is partly supported by the Research Grant for the RIKEN Genome Exploration Research Project from MEXT to Y.H. and the Grant for the RIKEN Frontier Research System, Functional RNA research program.
Proper citation: H-Invitational Database: Protein-Protein Interaction Viewer (RRID:SCR_008054) Copy
http://bioinf.uab.es/aggrescan/
Web-based tool for identifying hot spots of aggregation in polypeptides. Aggrescan uses an aggregation-propensity scale for natural amino acids derived from in vivo experiments and on the assumption that short and specific sequence stretches modulate protein aggregation. The algorithm is shown to identify a series of protein fragments involved in the aggregation of disease-related proteins and to predict the effect of genetic mutations on their deposition propensities. It also provides new insights into the differential aggregation properties displayed by globular proteins, natively unfolded polypeptides, amyloidogenic proteins and proteins found in bacterial inclusion bodies.
Proper citation: Aggrescan: The Hot Spot Finder (RRID:SCR_008403) Copy
DNAtraffic database is dedicated to be an unique comprehensive and richly annotated database of genome dynamics during the cell life. DNAtraffic contains extensive data on the nomenclature, ontology, structure and function of proteins related to control of the DNA integrity mechanisms such as chromatin remodeling, DNA repair and damage response pathways from eight model organisms commonly used in the DNA-related study: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Escherichia coli and Arabidopsis thaliana. DNAtraffic contains comprehensive information on diseases related to the assembled human proteins. Database is richly annotated in the systemic information on the nomenclature, chemistry and structure of the DNA damage and drugs targeting nucleic acids and/or proteins involved in the maintenance of genome stability. One of the DNAtraffic database aim is to create the first platform of the combinatorial complexity of DNA metabolism pathway analysis. Database includes illustrations of pathway, damage, protein and drug. Since DNAtraffic is designed to cover a broad spectrum of scientific disciplines it has to be extensively linked to numerous external data sources. Database represents the result of the manual annotation work aimed at making the DNAtraffic database much more useful for a wide range of systems biology applications. DNAtraffic database is freely available and can be queried by the name of DNA network process, DNA damage, protein, disease, and drug.
Proper citation: DNAtraffic (RRID:SCR_008886) Copy
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