Tools   Select Another Resource Report Type

http://wwwmgs.bionet.nsc.ru/mgs/systems/selex/

A database for the accumulation of experimental data on selected affinity-enriched sequences from different combinatorial libraries. During the last ten years, the novel technologies have been designed for identification of high affinity DNA and RNA sequences (ligands) to a wide variety of different targets, including nucleic acid binding proteins, peptides, and small organic molecules. Among these technologies are the following: SELEX (Systematic Evolution of Ligands by Exponential enrichment), SAAB (Selected And Amplified Binding site imprint assay), REPSA (Restriction Endonuclease Protection Selection and Amplification), CASTing (Cyclical Amplification and Selection of Targets) and other binding site selection procedures. In general, genetic analysis in vitro of the structural and functional properties of many nucleic acids was enhanced by the availability of methods for the amplification of nucleic acid sequences. Given current advance in sequencing whole genomes, combinatorial methods will be important in the next generation of studies, thus making the bridge between raw sequence data and actual biological processes. At present, enormous starting libraries are used in different SELEX processes and contain up to 1014?1015 sequences. Naturally, this information needs to be collected into public databases available via the Internet. The site sequences listed within the SELEX_DB may be used as independent control data in developing both novel methods for functional site recognition within gene sequences and recognition under concrete experimental conditions documented in the database. Additionally, information on functional site sequences and experimental conditions for their determination is useful for planning novel experiments applying SELEX technology.

Proper citation: SELEX DB (RRID:SCR_007921) Copy   

•   Source: SciCrunch Registry

http://recode.genetics.utah.edu

A compilation of programmed; translational recoding events taken from the scientific literature and personal communications. The database deals with programmed ribosomal frameshifting, codon redefinition and translational bypass occurring in a variety of organisms. The entries for each event include the sequences of the corresponding genes, their encoded proteins for both the normal and alternate decoding, the types of the recoding events involved, trans-factors and cis-elements that influence recoding.

Proper citation: RECODE- The database of the translational recoding events (RRID:SCR_007887) Copy   

•   Source: SciCrunch Registry

http://rapeseed.plantsignal.cn

The Shanghai Rapeseed Database contains genomic information about the Rapeseed plant. Resources available through the website include BLAST search functions, cDNA library construction, microarray hybridization, SAGE, and ethylmethanesulfonate (EMS) induced mutant population data. Multiple high-throughput genomic approaches were performed to study the gene expression profiles during Brassica napus (huyou-15) seed development and fatty acid (FA) metabolism, as well as the relevant regulation. Serial Analysis of Gene Expression (SAGE) using seed materials obtained a total of 68,716 tags, of which 23,895 were unique and 503 tags were functionally identified, and further revealed the transcriptome of approximately 35,000 transcripts in B. napus developing seeds. Further, ~22,000 independent ESTs were obtained by large-scale sequencing using immature embryos at different stages. 8462 uni-ESTs and 3526 full-length cDNAs were identified respectively, resulting in the systemic identification of B. napus FA biosynthesis-related genes. Gene expression profiles were further studied employing cDNA chip hybridization to reveal the global regulatory network of FA metabolism in developing seeds.

Proper citation: Shanghai Rapeseed Database (RRID:SCR_007923) Copy   

•   Source: SciCrunch Registry

http://ratmap.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented April 14, 2017. The Rat Genome Database RatMap is focused on presenting rat genes, DNA-markers, QTL's, etc. that is localized to chromosome. The database is dedicated to rat gene nomenclature and should be consulted for queries in such matters.

Proper citation: RatMap (RRID:SCR_007885) Copy   

•   Source: SciCrunch Registry

http://yeast.gi.k.u-tokyo.ac.jp/

The Saccharomyces Cerevisiae Morphological Database(SCMD) is a collection of micrographs of budding yeast mutants. Micorgraphs of mutants with altered cell morphology from a set of the haploid MATa deleted strains obtained from EUROSCARF. From the micrographs, disruptant cells are automatically extracted by our novel cell-image processing software.

Proper citation: SCMD - Saccharomyces cerevisiae Morphological Database (RRID:SCR_007881) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.sebida.de/

A database for the functional and evolutionary analysis of sex-biased genes. Sebida integrates data from multiple microarray studies comparing male versus female gene expression in D. melanogaster, D. simulans, and A. gambiae. In addition to the ratio of male to female (or testes to ovaries) expression for each gene, Sebida provides information useful for evolutionary studies, including measures of recombination, codon bias, and interspecific divergence.

Proper citation: SEBIDA: Sex Bias Database (RRID:SCR_007918) Copy   

•   Source: SciCrunch Registry

http://www.selenodb.org/

A database of eukaryotic selenoprotein genes, proteins, SECIS elements and related molecules. Selenoproteins are routinely mispredicted by automatic annotation systems and, therefore, misannotated in most genomic databases. We aim to provide correct annotations for the growing number of known selenoprotein genes. Current efforts are directed towards the construction of an initial set of genomic annotations in selected sequenced organisms using ad hoc computational tools and manually curated predictions. Computational approaches include ab initio and comparative gene prediction together with RNA secondary structure predictions.

Proper citation: SelenoDB (RRID:SCR_007919) Copy   

•   Source: SciCrunch Registry

http://ymbc.ym.edu.tw/sca_ensembl/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A candidate gene database for Spinocerebellar ataxia (SCA), which collected 3185 genes for 17 types of SCA. Those SCA subtypes that have known disease genes can be used as positive controls to optimize the parameters. The users may browse the candidate genes of a given SCA subtype by using the default parameters. The known disease genes were found to be the top three candidates using the default parameters. Alternatively, the users may score the candidate genes by changing the weight or the scores on the basis of their own working hypothesis.

Proper citation: SCAdb: A CANDIDATE GENE DATABASE FOR SPINOCEREBELLAR ATAXIAS (RRID:SCR_007915) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://interactome-cmp.ucsf.edu/

This database currently holds E-MAP scores (individual interactions and correlation coefficients) for budding yeast genes involved in the early secretory pathway and chromosome function (including DNA damage and repair, transcriptional control, chromosome segregation and telomere regulation). E-MAPs (Epistatic Mini Array Profiles) are formed by creating and quantifying high-density genetic interaction maps. With this method, observed double mutant colony sizes are compared to those that would be expected from a distribution of typical double mutant colonies of each strain. Each interaction is assigned a score, which indicates the magnitude of the difference from the expected value and the certainty of the score. Negative (or aggravating) scores (< -2.5) correspond to synthetic sick/lethal interactions while positive (or alleviating) scores (> +2.5) corresponds to epistatic or suppressor interactions.

Proper citation: Krogan Lab Interactome Database (RRID:SCR_008121) Copy   

•   Source: SciCrunch Registry

http://mrna.otago.ac.nz/

Database that provides access to mRNA sequences and associated regulatory elements that were processed from Genbank. These mRNA sequences include complete genomes, which are divided into 5-prime UTRs, 3-prime UTRs, initiation sequences, termination regions and full CDS sequences. This data can be searched for a range of properties including specific mRNA sequences, mRNA motifs, codon usage, RSCU values, information content, etc.

Proper citation: Transterm (RRID:SCR_008244) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://itfp.biosino.org/itfp/

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   

•   Source: SciCrunch Registry

http://wodaklab.org/iRefWeb/

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   

•   Source: SciCrunch Registry

http://pbil.univ-lyon1.fr/databases/homolens.php

Database of homologous genes from Ensembl organisms, structured under ACNUC sequence database management system. It allows to select sets of homologous genes among species, and to visualize multiple alignments and phylogenetic trees. It is possible to search for orthologous genes in a wide range of taxons. HOMOLENS is particularly useful for comparative sequence analysis, phylogeny and molecular evolution studies. More generally, HOMOLENS gives an overall view of what is known about a peculiar gene family. Note that HOMOLENS is split into two databases on this server: HOMOLENS contains the protein sequences while HOMOLENSDNA contains the nucleotide sequences. Protein sequences of HOMOLENS have been generated by translating the CDS of HOMOLENSDNA and using associated cross-references to generate the annotations.

Proper citation: Homologous Sequences in Ensembl Animal Genomes (RRID:SCR_008356) Copy   

•   Source: SciCrunch Registry

http://www.ingenuity.com/

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   

•   Source: SciCrunch Registry

http://nesg.org:9090/HCPIN/

The Human Cancer Pathway Protein Interaction Network (HCPIN) was constructed as a step toward better integrating protein three-dimensional (3D) structural information in cancer systems biology. It was constructed by analysis of several classical cancer-associated signaling pathways and their physical protein-protein interactions. The HCPIN Website provides a comprehensive description of this biomedically important multipathway network together with experimental and homology models of HCPIN proteins useful for cancer biology research.

Proper citation: Human Cancer Protein Interaction Network (RRID:SCR_008116) Copy   

•   Source: SciCrunch Registry

http://www.primervfx.com/#welcome

PrimerParadise is an online PCR primer database for genomics studies. The database contains predesigned PCR primers for amplification of exons, genes and SNPs of almost all sequenced genomes. Primers can be used for genome-wide projects (resequencing, mutation analysis, SNP detection etc). The primers for eukaryotic genomes have been tested with e-PCR to make sure that no alternative products will be generated. Also, all eukaryotic primers have been filtered to exclude primers that bind excessively throughout the genome. Genes are amplified as amplicons. Amplicons are defined as only one genes exons containing maximaly 3000 bp long dna segments. If gene is longer than 3000 bp then it is split into the segments at length 3000 bp. So for example gene at length 5000 bp is split into two segment and for both segments there were designed a separate primerpair. If genes exons length is over 3000 bp then it is split into amplicons as well. Every SNP has one primerpair. In addition of considering repetitive sequences and mono-dinucleotide repeats, we avoid designing primers to genome regions which contain other SNPs. -There are two ways to search for primers: you can use features IDs ( for SNP primers Reference ID, for gene/exon primers different IDs (Ensembl gene IDs, HUGO IDs for human genes, LocusLink IDs, RefSeq IDs, MIM IDs, NCBI gene names, SWISSPROT IDs for bacterial genes, VEGA gene IDs for human and mouse, Sanger S.pombe systematic gene names and common gene names, S.cerevisiae GeneBanks Locus, AccNo, GI IDs and common gene names) -you can use genome regions (chromosome coordinates, chromosome bands if exists) -Currently we provide 3 primers collections: proPCR for prokaryotic organisms genes primers -euPCR for eukaryotic organisms genes/exons primers -snpPCR for eukaryotic organisms SNP primers Sponsors: PrimerStudio is funded by the University of Tartu.

Proper citation: PrimerStudio (RRID:SCR_008232) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics2.wsu.edu/cgi-bin/Athena/cgi/home.pl

Athena is a web-based application that warehouses disparate datatypes related to the control of gene expression. Athena provides several features to enable exploration of the regulatory mechanisms of Arabidopsis gene control. The first main tool we provide is visualization of promoter domains of selected genes. Database crossreference for these transcription factors is provided as well as a statistical test for enrichment of binding activity within the set of selected promoters. The data mining tools in Athena allow for selection of sets of genes based on two different factors. -Genes can be select by specifying a set of binding factors whose putative sites must be present within all of those genes'' promoter regions. -Alternatively, genes can be selected using Gene Ontology annotations. Both GO (Gene Ontology) Slim terms and Gene Ontology terms are available. One can select a set of genes by either choosing a union of the genes annotated by a selected set of Slim terms or Gene Ontology terms. The selected gene''s putative binding factors are listed, including enrichment data. Furthermore, enriched presence of Gene Ontology terms is given. The analysis suite provides both enhanced data mining tools for selecting genes as well as several data displays., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Athena (RRID:SCR_008110) Copy   

•   Source: SciCrunch Registry