We support boolean queries, use +,-,<,>,~,* to alter the weighting of terms
A curated collection of all the trapped ES cell clones. Gene-trapping is a valuable tool that uses random mutagenesis to create hypomorphic or null alleles by insertion of exogenous DNA. Since numerous public and private projects have been performing gene trapping over the last few years,it is natural that large overlaps exist and some vectors produce better knock-outs than others due to their insertion site. Considering the high need to develop a comprehensive database that would include both public and private data to provide public access to this essential biological resource, we developed UniTrap, a curated collection of all the trapped ES cell clones, collected from public and private databases. We have developed a bioinformatics pipeline to automate the identification and characterization of trapped genes starting from their transcriptional sequence tags.We process gene trap sequence tags from ES cell clones to generate &lsquo;UniTraps&rsquo;, i.e. distinct collections of unambiguous insertions at the same subgenic region of annotated genes (RefSeq and Ensembl genes). The UniTrap resource contains data relative to well-known trapped genes. We aim to provide the wet lab researchers with a comprehensive, regularly updated database and curated tools for(i) identifying and comparing the clones carrying a trap into the genes of interest,(ii) evaluating the severity of the mutation to the protein function in each independent trapping event, and(iii) supplying complete information to perform PCR, RT-PCR and restriction experiments to verify the clone and identify the exact point of vector insertion.
A relational database containing all structural proteins of Arthropod cuticle identified to date. Many come from direct sequencing of proteins isolated from cuticle and from sequences from cDNAs that share common features with these authentic cuticular proteins. It also includes proteins from the five sequenced genomes where manual annotation has been applied to cuticular proteins: Anopheles gambiae, Apis mellifera, Bombyx mori, Drosophila melanogaster, and Nasonia vitripennis. Some sequences were confirmed as authentic cuticular proteins because protein sequencing revealed that they were present in cuticle; others were identified by sequence homology and other criteria. Entries provides information about whether sequences are putative or authentic cuticular proteins. CuticleDB was primarily designed to contain correct and full annotation of cuticular protein data. The database will be of help to future genome annotators. Users will be able to test hypotheses for the existence of known and also of yet unknown motifs in cuticular proteins. An analysis of motifs may contribute to understanding how proteins contribute to the physical properties of cuticle as well as to the precise nature of their interaction with chitin.
AAindex is a database of numerical indices representing various physicochemical and biochemical properties of amino acids and pairs of amino acids. AAindex consists of three sections now: AAindex1 for the amino acid index of 20 numerical values, AAindex2 for the amino acid mutation matrix and AAindex3 for the statistical protein contact potentials. All data are derived from published literature. An amino acid index is a set of 20 numerical values representing any of the different physicochemical and biological properties of amino acids. The AAindex1 section of the Amino Acid Index Database is a collection of published indices together with the result of cluster analysis using the correlation coefficient as the distance between two indices. This section currently contains 544 indices. Another important feature of amino acids that can be represented numerically is the similarity between amino acids. Thus, a similarity matrix, also called a mutation matrix, is a set of 210 numerical values, 20 diagonal and 20x19/2 off-diagonal elements, used for sequence alignments and similarity searches. The AAindex2 section of the Amino Acid Index Database is a collection of published amino acid mutation matrices together with the result of cluster analysis. This section currently contains 94 matrices. In the release 9.0, we added a collection of published protein pairwise contact potentials to AAindex as AAindex3. This section currently contains 47 contact potential matrices. Sponsors: This work was supported by grants and resources from the Ministry of Education, Culture, Sports, Science and Technology, and the Japan Science and Technology Agency, and the Bioinformatics Center, Institute for Chemical Research, Kyoto University and the Super Computer System, Human Genome Center, Institute of Medical Science, University of Tokyo.
An integrated genomic and functional genomic database providing access to genome-scale datasets for kinetoplastid parasites, and supporting a variety of complex queries driven by research and development needs. Currently, TriTrypDB integrates datasets from Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and T. cruzi. Users may examine individual genes or chromosomal spans in their genomic context, including syntenic alignments with other kinetoplastid organisms. Data within TriTrypDB can be interrogated utilizing a sophisticated search strategy system that enables a user to construct complex queries combining multiple data types. All search strategies are stored, allowing future access and integrated searches. ''''User Comments'''' may be added to any gene page, enhancing available annotation; such comments become immediately searchable via the text search, and are forwarded to curators for incorporation into the reference annotation when appropriate. TriTrypDB provides programmatic access to its searches, via REST Web Services. The result of a web service request is a list of records (genes, ESTs, etc) in either XML or JSON format. REST services can be executed in a browser by typing a specific URL. TriTrypDB and its continued development are possible through the collaborative efforts between EuPathDB, GeneDB and colleagues at the Seattle Biomedical Research Institute (SBRI).
FASTLINK is significantly modified and improved version of main programs of LINKAGE that runs much faster sequentially, can run in parallel, allows the user to recover gracefully from a computer crash, and provides abundant new documentation.
Database that provides comprehensive information about adverse effect targets of drugs described in the literature, including information about known drug adverse reaction targets, functions and properties. Moreover, proteins involved in adverse effect targets of chemicals not yet confirmed as adverse drug reaction (ADR) targets are also included as potential targets. Associated references are also included. This database gives physiological function of each target, binding drugs / agonists / antagonists / activators / inhibitors, IC(50) values of the inhibitors, corresponding adverse effects, and type of ADR induced by drug binding to a target. Cross-links to other databases are also introduced to facilitate the access of information about the sequence, 3-dimensional structure, function, and nomenclature of each target along with drug/ligand binding properties, and related literature. Each entry can be retrieved through multiple search methods including target name, target physiological function, adverse effect, ligand name, and biological pathways. A special page is provided for contribution of new or additional information. Function for ADR-target prediction by SVMDART: Submit protein primary sequence for ADR-related protein prediction.
The goals of Antibiotic Resistance Genes Database (ARGB) are to provide a centralized compendium of information on antibiotic resistance, to facilitate the consistent annotation of resistance information in newly sequenced organisms, and also to facilitate the identification and characterization of new genes. ARGB contains six types of database groups: - Resistance Type: This database contains information, such as resistance profile, mechanism, requirement, epidemiology for each type. - Resistance Gene: This database contains information, such as resistance profile, resistance type, requirement, protein and DNA sequence for each gene.This database only includes NON-REDUNDANT, NON-VECTOR, COMPLETE genes. - Antibiotic: This database contains information, such as producer, action mechanism, resistance type, for each gene. - Resistance Gene(NonRD): This database contains the same information as Resistance Gene. It does NOT include NON-REDUNDANT, NON-VECTOR genes, but includes INCOMPLETE genes. - Resistance Gene(ALL): This database contains the same information as Resistance Gene. It includes all REDUNDANT, VECTOR AND INCOMPLETE genes. - Resistance Species: This database contains resistance profile and corresponding resistance genes for each species. Furthermore, ARDB also contians three types BLAST database: - Resistance Genes Complete: Contains only NON-REDUNDANT, NON-VECTOR, COMPLETE genes sequences. - Resistance Genes Non-redundant: Contains NON-REDUNDANT, NON-VECTOR, COMPLETE, INCOMPLETE genes sequences. - Resistance Genes All: Contains all REDUNDANT, VECTOR, COMPLETE, INCOMPLETE genes sequences. Lastly, ARDB provides four types of Analytical tools: - Normal BLAST: This function allows an user to input a DNA or protein sequence, and find similar DNA (Nucleotide BLAST) or protein (Protein BLAST) sequences using blastn, blastp, blastx, tblastn, tblastx - RPS BLAST: A web RPSBLAST (RPS BLAST) interface is provided to align a query sequence against the Position Specific Scoring Matrix (PSSM) for each type. Normally, this will give the same annotation information as using regular BLAST mentioned above. - Multiple Sequences BLAST (Genome Annotation): This function allows an user to annotate multiple (less than 5000) query sequences in FASTA format. - Mutation Resistance Identification: This function allows an user to identify mutations that will cause potential antibiotic resistance, for 12 genes (16S rRNA, 23S rRNA, gyrA, gyrB, parC, parE, rpoB, katG, pncA, embB, folP, dfr). ������ :Sponsors: ARDB is funded by Uniformed Services University of the Health Sciences, administered by the Henry Jackson Foundation. :
The Structural Classification of Proteins (SCOP) database is a comprehensive ordering of all proteins of known structure, according to their evolutionary and structural relationships. Protein domains in SCOP are hierarchically classified into families, superfamilies, folds and classes. The continual accumulation of sequence and structural data allows more rigorous analysis and provides important information for understanding the protein world and its evolutionary repertoire. SCOP participates in a project that aims to rationalize and integrate the data on proteins held in several sequence and structure databases. As part of this project, starting with release 1.63, we have initiated a refinement of the SCOP classification, which introduces a number of changes mostly at the levels below superfamily. The pending SCOP reclassification will be carried out gradually through a number of future releases. In addition to the expanded set of static links to external resources, available at the level of domain entries, we have started modernization of the interface capabilities of SCOP allowing more dynamic links with other databases.
Portal to the PSORT family of computer programs for the prediction of protein localization sites in cells, as well as other datasets and resources relevant to localization prediction. The standalone versions are available for download for larger analyses.
Software package for analysis of brain imaging data sequences. Sequences can be a series of images from different cohorts, or time-series from same subject. Current release is designed for analysis of fMRI, PET, SPECT, EEG and MEG.
Software application (entry from Genetic Analysis Software)
Database of animal toxins, this most recent release (2009) focused on constructing a global-scale animal toxin-channel interaction network based on literature and database annotations through the integration of an ion channel database into ATDB 2.0. Most ion channel sequences were categorized and annotated with a hierarchic controlled term system (Ion Channel Ontology). More than 55,022 possible T-C interactions were extracted by text mining which link the toxin and ion channel database. These interaction data were classified carefully based on evidence type, in which 9,193 high confidence interactions were annotated in active site level. A web-based T-C interaction network view was build to visualize and make data access easy. The features and updates of ATDB 2.0 are summarized as follows: # AN interaction dataset including 55,022 toxin-channel interactions # Ion channel database (5,097 entries) # Ontology for ion channel classification (Ion Channel Ontology) # 3000 maps for toxins and ion channels interaction # More than 600 additional toxin entries # PDB view to visualize 3-D structure of molecule # More flexible option for data downloads. You may submit new toxins to the database.
A categorized list of bookmarks concerning neurobiology assembled by Professor Mark Dubin, Dept. of Molecular, Cellular and Developmental Biology, University of Colorado. Major categories include anatomy, computing, mental and physical conditions, general knowledge, mind, physiology, psychology, senses, and techniques.
Standard software package for genetic linkage called LINKAGE. Genetic linkage analysis is statistical technique used to map genes and find approximate location of disease genes.
Image Gallery of a 3D MRI Atlas of an Adult C57BL/6J Mouse Brain showing Slice Animation and 3D Animation including Axial, Coronal, Sagittal views. RealPlayer or Windows Media Player needs to be installed for viewing these animations.
NSDUH is the primary source of statistical information on the use of illegal drugs, alcohol, and tobacco by the U.S. civilian, noninstitutionalized population aged 12 or older. Conducted by the Federal Government since 1971, the survey collects data through face-to-face interviews with a representative sample of the population at the respondent''s place of residence. Correlates in OAS reports include the following: age, gender, pregnancy status, race / ethnicity, education, employment, geographic area, frequency of use, and association with alcohol, tobacco, & illegal drug use. NSDUH collects information from residents of households and noninstitutional group quarters (e.g., shelters, rooming houses, dormitories) and from civilians living on military bases. The survey excludes homeless persons who do not use shelters, military personnel on active duty, and residents of institutional group quarters, such as jails and hospitals. Most of the questions are administered with audio computer-assisted self-interviewing (ACASI). ACASI is designed to provide the respondent with a highly private and confidential mode for responding to questions in order to increase the level of honest reporting of illicit drug use and other sensitive behaviors. Less sensitive items are administered by interviewers using computer-assisted personal interviewing (CAPI). The 2010 NSDUH employed a State-based design with an independent, multistage area probability sample within each State and the District of Columbia. The eight States with the largest population (which together account for about half of the total U.S. population aged 12 or older) were designated as large sample States (California, Florida, Illinois, Michigan, New York, Ohio, Pennsylvania, and Texas) and had a sample size of about 3,600 each. For the remaining 42 States and the District of Columbia, the sample size was about 900 per State. The design oversampled youths and young adults; each State''s sample was approximately equally distributed among three age groups: 12 to 17 years, 18 to 25 years, and 26 years or older.
A brain bank of the United Kingdom which collects human brains for Parkinsons disease research. The collection is comprised of brain, spinal cord and a sample of cerebrospinal fluid from people with and without Parkinson's after death. Researchers can fill out a brain tissue request form to order samples from the bank.
The goal of this project is to aid genetic association studies of addiction by creating a resource of biologically relevant genes, pathways and single nucleotide polymorphisms (SNPs). The primary users of the NeuroSNP resource are investigators conducting genome-wide association studies (GWASs) of addiction-related phenotypes. NeuroSNP will allow investigators to identify biologically relevant genes for addiction based on curated expert knowledge, and assess the coverage of these genes provided by commercial SNP microarrays. If investigators wish to ensure the coverage of certain addiction-related genes is optimal, NeuroSNP provides a mechanism for supplementation. While commercial SNP microarrays offer affordable and comprehensive coverage of the human genome, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is believed to be influenced by complex interactions involving several genes and pathways. NIDA has assembled a number of investigators specializing in fields such as genetics, pharmacogenetics, bioinformatics and neurobiology through a Request for Information. These investigators have pooled their expert knowledge to produce a database of addiction-related genes and SNPs. Commercial SNP microarrays, such as those offered by Affymetrix and Illumina, are then analyzed to determine how well certain addiction-related genes are covered. When the coverage is less than optimal, a SNP prioritization scheme is used to supplement the commercial array with the most biologically informative markers. For example, SNPs in coding regions, promoters, and evolutionary conserved regions are selected first.
A stand-alone, open source human cortical meta-analysis and visualization toolbox for MatLab. It projects stereotaxic coordinates to a mean cortical surface by using an anatomical database of 60 young adults to provide multiple mappings of normalized cortical surfaces into MNI space. VAMCA performs the following analyses: # Multi-Fiducial Projection Mapping: Map stereotaxic 3D coordinates to the normalized cortical location for each of 60 database subjects. # Computing Centroid Locations for groups of foci both on a mean cortical surface and in MNI space. # Comparing Two Groups of Foci for differences in location (surface or 3D) of their group centroids and computing the groups' overlap extent using permutation tests. # Detecting Significant Densities of Foci or Density Differences of Two Groups within anatomical ROIs on a mean cortical surface by using Monte Carlo analyses. Coordinate weights allow fixed or random effects type analyses.
Database that represents a centralized platform to visually depict and integrate information pertaining to domain architecture, post-translational modifications, interaction networks and disease association for each protein in the human proteome. All the information in HPRD has been manually extracted from the literature by expert biologists who read, interpret and analyze the published data.