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http://www.modelling.leeds.ac.uk/sb/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A database of known ligand binding sites within the PDB which is navigable by PDB identifier or ligand 3 letter code e.g. NAD. Each binding site has a frequently updated register of structurally similar binding sites sharing atomic similarity detected by geometric hashing. Multiple alignments, structural superpositions and links to other structural databases are also available enabling further analysis. The rapid expansion of structural information for protein-ligand binding sites is potentially an important source of information in structure-based drug design and in understanding ligand cross reactivity and toxicity. We have developed a large database of ligand binding sites extracted automatically from the Protein Data Bank. This has been combined with a method for calculating binding site similarity based on geometric hashing to create a relational database for the retrieval of site similarity and binding site superposition. It contains an all-against-all comparison of binding sites and holds known protein-ligand binding sites, which are made accessible to data mining. Here we demonstrate its utility in two structure-based applications: in determining site similarity and in aiding the derivation of a receptor-based pharmacophore model.

Proper citation: SitesBase (RRID:SCR_007932) Copy   

•   Source: SciCrunch Registry

http://egg.umh.es/databases.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 25, 2013. RISSC is a database of ribosomal 16S-23S spacer sequences intended mainly for molecular biology studies in typing, phylogeny and population genetics. Ribosomal spacers have proven to be extremely useful tools for typing and identifying closely related prokaryotes due to their high variability in size and/or sequence, much more so than the flanking 16S and 23S rRNA genes. These genes are commonly used to establish molecular relationships among microbes at a taxonomic level of species or higher (e.g genus, domain...). However their internal transcribed spacers (ITS) are much more useful to discriminate at the species or even strain level. Currently, many published papers are showing the growing importance of these regions of the ribosomal operon in these types of studies. A second, much shorter, ribosomal spacer can be found between rRNA genes 23S and 5S, also of phylogenetic interest. We intend to incorporate them into the database in the near future. By creating RISSC, our intention is to provide the scientific community with a comprehensive set of ribosomal spacer sequences, fully edited and characterized with a key feature as is the presence/absence of tRNA genes within them, ready to be used and compared with their own ITS sequences.

Proper citation: RISSC - Ribosomal Internal Spacer Sequence Collection (RRID:SCR_007898) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/sky/

The SKY/M-FISH and CGH databases provide a public platform for investigators to share and compare their molecular cytogenetic data. The database is open to everyone and all users can view an individual investigator's public data or compare public cases from different investigators. Those wishing to contribute their own data must register and can choose to keep their data private for a period not to exceed two years. Spectral Karyotyping (SKY), Multiplex Fluorescence In Situ Hybridization (M-FISH) and Comparative Genomic Hybridization (CGH) are complementary fluorescent molecular cytogenetic techniques. SKY/M-FISH permits the simultaneous visualization of each human or mouse chromosome in a different color, facilitating the identification of chromosomal aberrations. CGH utilizes the hybridization of differentially labeled tumor and reference DNA to generate a map of DNA copy number changes in tumor genomes.

Proper citation: SKY/M-FISH/CGH (RRID:SCR_007933) Copy   

•   Source: SciCrunch Registry

http://sisyphus.mrc-cpe.cam.ac.uk

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. A collection of manually curated protein structural alignments and their interrelationships. Each multiple alignment within the SISYPHUS database consists of structurally similar regions common to a group of proteins. These regions range from oligomeric biological units, or individual domains to fragments of different size representing either internal structural repeats or motifs common to structurally distinct proteins. The SISYPHUS multiple alignments are displayed with SPICE, a browser that provides an integrated view of protein sequences, structures and their annotations.

Proper citation: SISYPHUS (RRID:SCR_007930) Copy   

•   Source: SciCrunch Registry

http://RiceGAAS.dna.affrc.go.jp/

A rice genome automated annotation system. This system integrates programs for prediction and analysis of protein-coding gene structure. Integrated softwares are coding region prediction programs ( GENSCAN, RiceHMM, FGENESH, MZEF ), splice site prediction programs (SplicePredictor ), homology search analysis programs ( Blast, HMMER, ProfileScan, MOTIF ), tRNA gene prediction program ( tRNAscan-SE ), repetitive DNA analysis programs ( RepeatMasker, Printrepeats ), signal scan search program ( Signal Scan ), protein localization site prediction program ( PSORT ), and program of classification and secondary structure prediction of membrane proteins ( SOSUI ). Blast against full-length cDNA sequences of japonica rice is integrated. The full-length rice cDNA sequence is provided by KOME database. Interpretation of the coding region is fully automated and gene prediction is accomplished without manual evaluation and modification. Therefore some differences exist between the predicted genes by the system and the manually predicted genes included in the GenBank entries. Please see "comparison table of gene prediction", http://RiceGAAS.dna.affrc.go.jp/rga-bin/col_accur.pl in detail. Further, a unique function is automatically assigned for predicted gene by GFSelector based on the protein homology of the gene. Additionally, the keyword search from the functions predicted by GFSelector is provided.

Proper citation: RiceGAAS (RRID:SCR_007896) Copy   

•   Source: SciCrunch Registry

http://retroryza.fr/

This database provides some information and resources related to LTR-retrotransposons in rice genome. The availability of the pseudomolecules of the Asian cultivated rice (Oryza sativa ssp. japonica cv. Nipponbare) allowed the construction, for the first time, of a non-redundant database of LTR retrotransposon sequences for an agronomically important plant species. 242 distinct families are curated, of which 194 have not been described elsewhere. These newly identified sequences, representing mainly low copy number elements, were identified by in-silico approaches. Reference molecules of each LTR retrotransposon family were characterized, annotated and deposited in RetrOryza. Further analysis will be focused on the identification and the annotation of LTR retrotransposons of several species within the Oryza genus.

Proper citation: RetrOryza.org (RRID:SCR_007890) Copy   

•   Source: SciCrunch Registry

http://sirna.cgb.ki.se

This is a site with links to several siRNA services, including siRNA base sequence searches, specificity searches, known siRNA molecule searches, and target sequences. One of the sites, called siSVM, allows users to predict efficacy of siRNAs given their base sequence using features derived from the siRNA sequence. siSVM is designed to allow common methods of siRNA design to be included in the search. This includes motif rules,energy conditions and specificity searching. The second site it links to, siRNA specificity prediction, allows users to perform a specificity search for siRNAs to avoid off-target effects. SpecificityServer is designed to help you identify potential non-specific matches to your siRNA. It incorporates the latest information about non-specific matches (sequence-specific only). The third site it links to, siRNAdb, is a database of known siRNA molecules. It provides a list of sirnaID, target, geneID, geneAcc, TargetStart, and targetEnd.Category: RNA sequence databases

Proper citation: siRNAdb (RRID:SCR_007929) Copy   

•   Source: SciCrunch Registry

http://sirecords.umn.edu/siRecords/

On this site, you can search siRNA records, design siRNAs, or submit siRNA records resulting from your own study (requires register/login). Small interfering RNAs (siRNAs) are a class of 20-25 nucleotide-long double-stranded RNAs, and they are widely used as gene knock-down tool in molecular genetics, functional genomics, and drug discovery studies. However, despite numerous efforts, the design of potent siRNA remains inadequate. Design rules resulting from different studies often disagree with each other, and are often unsatisfactory. Typically, only about 75-80% siRNAs designed based on current rules result in >50% knock-down efficacy. Observing these difficulties, we have established this database of experimentally validated mammalian siRNAs with efficacy ratings. As of August 18, 2008, 17,192 records of experimentally validated siRNAs, targeting 5,086 genes, originated from 6,122 independent studies are hosted in siRecords.

Proper citation: siRecords (RRID:SCR_007928) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/simap/

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   

•   Source: SciCrunch Registry

http://silkworm.genomics.org.cn/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 20,2019.A database of integrated genome resources for the silkworm, Bombyx mori. This database provides access to not only genomic data including functional annotation of genes, gene products and chromosomal mapping, but also extensive biological information such as microarray expression data, ESTs and corresponding references. SilkDB will be useful for the silkworm research community as well as comparative genomics. Recently, an international collaboration has been launched to assemble a complete silkworm genome sequence, which is based on the 6� and 3� draft genome sequences created by Chinese group and Japanese group in 2004 (Mita et al., 2004; Xia et al., 2004), respectively. The genome assembly quality has been greatly improved. Base on a high density SNP genetic map, over 80% of genome sequence could be mapped on 28 chromosomes of the silkworm. The first version of SilkDB was released in 2004. Since that time, the silkworm has become a focus in insect research community and the study of silkworm has been greatly accelerated. Now, we are happy to announce the release of a new version of SilkDB, which updated all of the data, added new information of genome sequence and genes, and provides new tools to facilitate use of the genome database.

Proper citation: SilkDB (RRID:SCR_007926) Copy   

•   Source: SciCrunch Registry

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://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://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