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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.

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 17 years ago - by Anonymous

A database of funding opportunities from both public and private funding sources. Search by keyword and the funding opportunities matching your criteria are displayed. Click on the funding title to view the complete record. You may also add opportunities to the ResearchCrossroads database if you have registered.

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. A database of predicted specificity-determining residues in protein families. Predicted positions may have been used during evolution to change the function of proteins within a protein family. These positions are excellent targets for mutational studies and should lead to a better understading of protein function. SDR uses the PFAM database of protein domains for sequence alignments and domain definitions as well as the GPCR database for G-protein coupled receptors.

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• SciCrunch
• 17 years ago - by Anonymous

SCOPPI is a database of all domain-domain interactions and their interfaces derived from PDB structure files and SCOP domain definitions. Interfaces are classified according to the geometry of the domain associations and are annotated with various interaction characteristics. Screenshots of all interfaces are available. More than 4,000 distinct types of domain interfaces are collected from Protein Quaternary Structure Server and Protein Data Bank. Given a pair of interacting domains, we define face as the set of interacting residues in each single domain and the pair of interacting faces as an interface. We investigate how the geometry of interfaces relates to a network of interacting protein families, such as how many different binding orientations are possible between two families or whether a family uses distinct surfaces or the same surface when the family has diverse interaction partners from various families. We show there are, on average, 1.2-1.9 different types of interfaces between interacting domains and a significant number of family pairs associate in multiple orientations. In general, a family tends to use distinct faces for each partner when the family has diverse interaction partners. Each face is highly specific to its interaction partner and the binding orientation. The relative positions of interface residues are generally well conserved within the same type of interface even between remote homologs.

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 17 years ago - by Anonymous

SBASE is a database of protein domain sequences collected from the literature, from protein sequence databases and from genomic databases. The protein domains are defined by their sequence boundaries given by the publishing authors or in one of the primary sequence databases (Swiss-Prot, PIR, TREMBL etc.). Domain groups are included if they have well defined sequence boundaries, and if they can be distinguished from other sequences using a similarity search technique. The SBASE database uses a set theoretical approach for representing similarities, which in practical terms is extremely simple. Sequences are considered similar if they are members of a similarity group in which all or most sequences are similar to each other and less similar to other members of the database. Sequences that have an above threshold BLAST similarity score to at least one member of the group is called the neighbourhood of the group. The below sketch shows such a neighborhood; the similarities within the group (self-similarities) and those pointing to non-member neighbours (non-self similarities) are shown in different colours., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 17 years ago - by Anonymous

The graduate program in Neuroscience is a multidisciplinary, interdepartmental program divided into three main areas: Cell and Molecular Neuroscience, Development and Regeneration, and Systems Neuroscience. Their research relates to many human diseases and disorders including fetal alcohol syndrome, spinal cord injury, degenerative retinal disease, Alzheimer''s disease, multiple sclerosis, cerebral palsy, and amyotrophic lateral sclerosis (ALS), also known as Lou Gehrig''s disease.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 9, 2014. SARS-CoV RNA SSS DATABASE is a database of the predicted RNA secondary structural sequences of six SARS coronaviruse complete genomes. These structures were sequenced and submitted to GenBank by the separate sequencing and research groups from countries and areas, including Beijing, Hong Kong, Taiwan, USA, Canada, and Germany. The database provides the detailed information of all the possible hairpin loops, interior loops, bulge loops, multi-branched loops, double-stranded stems, and free unpaired nucleotides of RNA secondary structural sequences of six SARS isolates, BJ01(Accession: AY278488), CUHK-AG01 (Accession: AY345986), TWY (Accession: AP006561), Urbani (Accession: AY278741), TOR2 (Accession: AY274119), and Frankurt 1 (Accession: AY291315). . The ORIGIN sequences in the database are from the NCBI's GenBank.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. The S4 database contains sequence alignments of domains in SCOP superfamilies. The aligned domains are selected using ASTRAL so that no two domains in the alignment have more than 40 percent identity and, moreover, they align all domains identified by ASTRAL as having less than 40 percent sequence identity. The alignments are generated using information from pairwise structural alignments of all domains in a given superfamily. These structural alignments generate residue equivalences and distances between residues, as well as an overall similarity of the two domains being compared (RMSD). This information is used to score individual the equivalences between residues. The scores are then integrated using a multiple sequence alignment program to generate the finished alignment. This database allows alignments to be retrieved in clustal format, or viewed in a web browser, with either structural or sequence features annotated. In addition, the statistics of structural diversity for each superfamily can be seen. The pairwise structural alignments were performed using the SAP program. The output of SAP was converted to a T-Coffee library so that the multiple sequence alignment T-Coffee could be use to compute the sequence alignments.

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• SciCrunch
• 17 years ago - by Anonymous

It collects information about scaffold/matrix attached regions and the nuclear matrix proteins that are supposed be involved in the interaction of these elements with the nuclear matrix. It covers the whole range from yeast to human. The SMAR table gives information on individual sequence elements of experimentally proven matrix binding activity. In release 2.3 it contains 500 entries. The sequences therein can be assigned to more than 150 genes from eukaryotic species ranging from yeast to human. The SMARbinder table contains 96 entries (release 2.3), but this figure does not reflect the number of independent S/MAR binding proteins. First of all, homologous factors from different species such as human and mouse SATB1 are given in different entries since they may differ in some aspects. Moreover, products of distinct but very similar genes or alternative splice products are included as separate entries. In some cases a more general term defining a S/MAR-binding activity may appear as one entry eventhough it might be composed of two or more subunits. The SMARbinder table will only contain those proteins of nuclear localization for which an interaction with a well defined S/MAR has been shown. Besides that the SMARbinder table will also include proteins that are proven components of the the salt-resitent (LIS-resistent) nuclear matrix. Gene entries, besides of giving the gene name in a long and a short (abbreviated) denomination, collect all links to individual S/MARs given in S/MARt DB and/or provide pointers to "S/MARbinders". The entries also contain links to transcription factor binding sites listed in TRANSFAC and give a link to the corresponding TRRD entry describing the regulatory features of the gene on different hierarchical levels.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 19, 2016. It is a database dedicated to Receptor Tyrosine Kinase. The RTKdb is the web-based interface of the RTKdb which is a database containing all the protein sequences of RTK, organized into families. It allows one to select sets of homologous genes from different species (only common species for the moment) and to visualize multiple alignments and phylogenetic trees. Thus the RTKdb is particularly useful for comparative genomics, phylogeny and molecular evolution studies. It contains a total of 159 proteins.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Database of high throughput insertional mutagenesis screening projects of retroviral and transposon insertional mutagenesis in mouse tumors. Information in the RTCGD is obtained from sequence comparison by using public databases UCSC genome mm9 browser. Data based on previous genome assembly mm8 is also available at RTCGD mm8. MCGP has developed three web search tools including Easy Search to query proviral integration sites using mouse gene symbol of gene name; Model Search to obtain RIS information based on tumor models and/or tumor types; Interaction Search to find gene-to-gene interaction. It displays the list of genes which reside in the same tumor to your gene of interest.

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• SciCrunch
• 17 years ago - by Anonymous

Central repository for high quality frequently updated manual annotation of vertebrate finished genome sequence. Human, mouse and zebrafish are in the process of being completely annotated, whereas for other species the annotation is only of specific genomic regions of particular biological interest. The majority of the annotation is from the HAVANA group at the Welcome Trust Sanger Institute. Users can BLAST, search for specific text, export, and download data. Genomes and details of the projects for each species are available through the homepages for human mouse and zebrafish. The website is built upon code from the EnsEMBL (http://www.ensembl.org) project. Some Ensembl features are not available in Vega. From the users point of view perhaps the most significant of these is MartView. However due to their inclusion in Ensembl, Vega human and mouse data can be queried using Ensembl MartView. Vega contains annotation of the human MHC region in eight haplotypes, and the LRC region in three haplotypes. Vega also contains annotation on the Insulin Dependent Diabetes (IDD) regions on non-reference assemblies for mouse.

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• SciCrunch
• 16 years ago - by Anonymous

It is a database that details the interactions of extruded, unpaired RNA nucleotide bases. It presents and classifies the protein binding pockets that accommodate them, and also allows the recognition of similar protein binding patters involved in interactions with different RNA molecules. Given an unbound structure of a target protein, it allows the prediction of its RNA nucleotide binding sites. The goal of this database is to describe, classify, and predict the interactions between protein binding sites and single-stranded RNA bases. Specifically, RsiteDB describes the protein binding pockets that accommodate extruded nucleotides not involved in RNA base pairing. RsiteDB has two modes of operation. Analysis and classification of protein-RNA interactions: Given a protein-RNA complex RsiteDB analyzes its nucleotide and dinucleotide binding sites. It details the properties of the protein binding pockets that accommodate these extruded nucleotides and presents a list of proteins with similar binding pockets. These proteins may have a totally different overall sequences and structural folds. RsiteDB details and visualizes the features shared by all the binding sites classified to the same cluster. Prediction of RNA dinucleotide binding sites: Given a target, potentially unbound, protein structure we search its surface for regions similar to the created 3-D consensus binding patterns of RNA dinucleotides. The recognized regions are predicted to serve as binding sites. Using leave-one-out tests, the success rate of these predictions was estimated to be about 80%. It must be noted that currently we do not aim to predict whether a protein can bind RNA; rather, given an unbound RNA binding protein, our goal is to predict its binding sites and their modes of interaction. In addition, due to a low number of single nucleotide clusters, currently, we do not use them for the prediction.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 19, 2016. It is a curated database that catalogs the numbers of genes that encode for 16S, 23S and 5S ribosomal RNAs in Bacteria and Archaea. Typically, a single copy of each of these genes is clustered into a rRNA operon, with as many as 15 rRNA operons present per genome. The genomic locus for any of the rRNA encoding genes is ?rrn? ? hence the name of this database. Because the number of genes encoding tRNAs is positively correlated with the number of rRNA-encoding genes (1), tRNA gene copy number is also cataloged in the rrnDB. Data are gathered both from sequenced genomes and from published articles that include estimates of the number of rRNA encoding genes.

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• SciCrunch
• 17 years ago - by Anonymous

It is a database that provides detailed information about ribosomal protein (RP) genes. It contains data from humans and other organisms. Users can search this database by gene name and organism. Each record includes sequences (genomic, cDNA, and amino acid sequences), intron/exon structures, genomic locations, and information about orthologs. In addition, users can view and compare the gene structures from different organisms and make multiple amino acid sequence alignments. RPG also provides information on small nucleolar RNAs (snoRNAs) that are encoded in the introns of RP genes.

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• SciCrunch
• 17 years ago - by Anonymous