Curator Dashboard

CPODES is a numerical integrator for solving multibody dynamics problems using coordinate projection. It is based on the CVODES integrator which is part of the DOE Sundials suite. It is a multistep integrator providing variable order Adams (up to 12th order) and BDF (up to 5th order) methods for non-stiff problems and BDF (up to 5th order) for stiff problems. It uses CVODES to advance the ODE, and then performs coordinate projection back to the constraint manifold to exactly solve the DAE. The projection is also incorporated back into the error test where it permits larger steps. Binaries of this software are bundled with other SimTK Core modules.

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• 17 years ago - by Anonymous

A versatile 1D, 2D and 3D data viewer geared for cross-platform visualization of stereotactic brain data. It is a 3-D viewer that allows volumetric data display and manipulation of axial, sagittal and coronal views. It reads Analyze, Raw-binary and NetCDF volumetric data, as well as, Multi-Contour Files (MCF), LWO/LWS surfaces, atlas hierarchical brain-region labelings ( Brain Trees). It is a portable Java-based software, which only requires a Java interpreter and a 64 MB of RAM memory to run on any computer architecture. LONI_Viz allows the user to interactively overlay and browse through several data volumes, zoom in and out in the axial, sagittal and coronal views, and reports the intensities and the stereo-tactic voxel and world coordinates of the data. Expert users can use LONI_Viz to delineate structures of interest, e.g., sulcal curves, on the 3 cardinal projections of the data. These curves then may be use to reconstruct surfaces representing the topological boundaries of cortical and sub-cortical regions of interest. The 3D features of the package include a SurfaceViewer and a full real-time VolumeRenderer. These allow the user to view the relative positions of different anatomical or functional regions which are not co-planar in any of the axial, sagittal or coronal 2D projection planes. The interactive part of LONI_Viz features a region drawing module used for manual delineation of regions of interest. A series of 2D contours describing the boundary of a region in projection planes (axial, sagittal or coronal) could be used to reconstruct the surface-representation of the 3D outer shell of the region. The latter could then be resliced in directions complementary to the drawing-direction and these complementary contours could be loaded in all tree cardinal views. In addition the surface object could be displayed using the SurfaceViewer. A pre-loading data crop and sub-sampling module allows the user to load and view practically data of any size. This is especially important when viewing cryotome, histological or stained data-sets which may reach 1GB (109 bytes) in size. The user could overlay several pre-registered volumes, change intensity colors and ranges and the inter-volume opacities to visually inspect similarities and differences between the different subjects/modalities. Several image-processing aids provide histogram plotting, image-smoothing, etc. Specific Features: * Region description DataBase * Moleculo-genetic database * Brain anatomical data viewer * BrainMapper tool * Surface (LightWave objects/scenes) and Volume rendering tools * Interactive Contour Drawing tool Implementation Issues: * Applet vs. Application - the software is available as both an applet and a standalone application. The former could be used to browse data from within the LONI database, however, it imposes restrictions on file-size, Internet connection and network-bandwidth and client/server file access. The later requires a local install and configuration of the LONI_Viz software * Extendable object-oriented code (Java), computer architecture independent * Complete online software documentation is available at http://www.loni.ucla.edu/LONI_Viz and a Java-Class documentation is available at http://www.loni.ucla.edu/~dinov/LONI_Vis.dir/doc/LONI_Viz_Java_Docs.html

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• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. C++ long-read aligner for PacBio reads., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• 12 years ago - by Anonymous

A database for maternal gene expression information for ascidia, colloquially known as sea squirts. Information available includes DNA sequences, expression patterns of ESTs, and cDNA data from uncleaved fertilized eggs. The goal is to utilize the database to understand molecular mechanisms of establishment of embryonic body plans of chordates and to understand evolution from invertebrates to vertebrates in the future.

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• 17 years ago - by Anonymous

This website contains a lot of images and slides of the nervous system. Most images are of the central nervous system histology and peripheral nervous system histology. Computation Neuroscience

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• 17 years ago - by Anonymous

A division of the Stanford University Libraries, which produces the online versions of journals and other scholarly content.

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A database of conserved sequence elements, identified by a systematic genomic sequence comparison between a set of human genes involved in the pathogenesis of genetic disorders and their murine counterparts. Human and mouse genomic sequences were compared by BLASTZ. Sequences longer than 100 and with identity better than 70 were selected as CSTs and imported into the database. CSTs are extensively annotated with respect to exon/intron structure and other biological parameters. CST counterparts in other species were identified by using BLAST to scan genomes from other species, and selecting on the basis of homology and co-linearity. The database can be accessed by gene, chromosomal location, graphic browser, DNA features, and coding regions.

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• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. This database is intended to serve as a learning tool to obtain curated information for the design of microarray targets to scan collecting duct tissues (human, rat, mouse). The database focuses on regulatory and transporter proteins expressed in the collecting duct, but when collecting duct proteins are a member of a larger family of proteins, common additional members of the family are included even if they have not been demonstrated to be expressed in the collecting duct. An Internet-accessible database has been devised for major collecting duct proteins involved in transport and regulation of cellular processes. The individual proteins included in this database are those culled from literature searches and from previously published studies involving cDNA arrays and serial analysis of gene expression (SAGE). Design of microarray targets for the study of kidney collecting duct tissues is facilitated by the database, which includes links to curated base pair and amino acid sequence data, relevant literature, and related databases. Use of the database is illustrated by a search for water channel proteins, aquaporins, and by a subsequent search for vasopressin receptors. Links are shown to the literature and to sequence data for human, rat, and mouse, as well as to relevant web-based resources. Extension of the database is dynamic and is done through a maintenance interface. This permits creation of new categories, updating of existing entries, and addition of new ones. CDDB is a database that organizes lists of genes found in collecting duct tissues from three mammalian species: human, rat, and mouse. Proteins are divided into categories by family relationships and functional classification, and each category is assigned a section in the database. Each section includes links to the literature and to sequence information for genes, proteins, expressed sequence tags, and related information. The user can peruse a section or use a search engine at the bottom of the web page to search the database for a name or abbreviation or for a link to a sequence. Each entry in the database includes links to relevant papers in the kidney and collecting duct literature. It uses links to PubMed to generate MEDLINE searches for retrieval of references. In addition, each entry includes links to curated sequence data available in LocusLink. Individual links are made to sequence and protein data for human, rat, and mouse. Links are then added as curated sequences become available for proteins identified in the renal collecting duct and for proteins identified in kidney and similar in function or homologous to proteins identified in the collecting duct.

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• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on September 23,2022. The Arabidopsis Mitochondrial Protein Database is an Internet-accessible relational database containing information on the predicted and experimentally confirmed protein complement of mitochondria from the model plant Arabidopsis thaliana. This database, and the proteomic data contained in it for Arabidopsis mitochondria, have been accepted for publication in The Plant Cell.

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• 17 years ago - by Anonymous

Science Commons, OBO Foundry, and several other groups working with biological information on the Semantic Web have initiated an effort to establish shared community-maintained URIs for important data integration points such as life sciences database records (example: the record in the Entrez Gene database that has GeneID 1003064). We are attempting to determine the right technical and organizational recipe that will lead to the uptake of these URIs by a as many RDF-using bioinformatics projects as possible. Were this to be a success, one would be able to mash up information from multiple sources in a wide variety of ways, using the shared URIs to forge links between pieces. Information could be extracted from one source for inclusion in another; information could be combined in SPARQL queries using multiple FROM clauses; extractions from several triple stores could be combined to create a new one. Without shared URIs, this kind of integration would still be possible, but it would be significantly more difficult as it would require some kind of plumbing or mapping to get the two result sets to link up. Requirements We are limiting our concern for now to URIs for records in databases mentioned in external links from the Gene Ontology (GO), such as those from Enzyme or Pfam, with possible extension to other databases such as those in the LSRN (Life Science Resource Name) registry. The URIs we propose are meant to serve the community of Semantic Web-enabled bioinformatics projects that need URIs that refer to or denote database records. We identify the following requirements for URIs to serve a community and to be shared among Semantic Web projects: 1. It must be clearly stated what the intended referent of each URI is supposed to be, i.e. that the URI denotes some particular record from some particular database. 2. Information about the URI and its referent, including such a statement, must be made available, and in order to leverage existing protocol stacks, it must be obtainable via HTTP. (We'll call such information URI documentation.) 3. URI documentation must be provided in RDF. 4. Provision of URI documentation must be an ongoing concern. The ability to provide it may have to outlive the original database or the database's creator. 5. The provider of the URI documentation must be responsive to community needs, such as the need to have mistakes fixed in a timely manner. 6. URI documentation must be open so that it can be replicated and reused. Control of shared URIs should be in the hands of those who depend on them. This is the best way to ensure that the URIs serve the community in the ways listed above. Overall design The idea is to manage a server, or a set of servers, that can deliver appropriate RDF documents for the shared URIs. An HTTP GET of a URI would retrieve not the database record itself, but rather one of these RDF documents (perhaps via a 303 redirect). The RDF document will include the following: 1. Documentation specifying what the URI denotes (URI documentation), including an rdf:type, the database that the record comes from, and the record's identifier or key within that database. 2. Links to the various encodings of the record provided by the data provider, e.g. XML, ASN, HTML for the NCBI databases and so on. Each of these encodings would in turn have its own URI naming that particular encoding of the record, the main URI being the name of the record without commitment as to encoding. 3. Links as appropriate to corresponding resources belonging to semantic web projects participating in the common naming scheme, e.g. http://bio2rdf.org/pmid:15456405. 4. Links as appropriate to related external resources that build on the database record. For example, the RDF for PubMed record 15456405 could link out to the iHOP page for the article described by the PubMed record. 5. Other information related to the record that might be of use to a human reader or automated agent. External links can be represented rigorously in RDF, allowing programs that access the RDF to proceed deterministically not only to the various encodings but also to any of the various related resources. This might be accomplished by having a distinct property for each participating project, or in some other way. We do not generally expect the RDF to include any of the content of the database record, although there is no particular reason to rule this out (except in cases where license terms preclude it). science, commons, biological, bioinformatic, naming

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• 17 years ago - by Anonymous

A database of antibody structure containing sequences from Kabat, IMGT and the Protein Databank (PDB), as well as structure data from the PDB. It provides search of the sequence data on various criteria and display of results in different formats. For data from the PDB, sequence searches can be combined with structural constraints. For example, one can ask for all the antibodies with a 10-residue Kabat CDR-L1 with a serine at H23 and an arginine within 10A of H36. The site also has software for structure analysis and other information on antibody structure available.

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• 17 years ago - by Anonymous

Interolog/Regulog quantitatively assess the degree to which interologs can be reliably transferred between species as a function of the sequence similarity of the corresponding interacting proteins.

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• 17 years ago - by Anonymous

The database NPIDB (Nucleic acid Protein Interaction DataBase) contains information derived from structures of DNA-protein and RNA-protein complexes extracted from Protein Data Bank (PDB) (1932 complexes in the end of 2007). It is equipped with a web-interface and a set of tools for extracting biologically meaningful characteristics of complexes. They are committed to satisfy all potential database users in order to: 1. Provide an essential information on structural features of DNA-protein and RNA-protein interaction for the users who need to get acquainted with the problem. 2. Give an effective access to the reasonably structured information about all DNA-protein and RNA-protein complexes containing in PDB. 3. Allow all visitors a quick access to our own research.

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• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database of genetic and gene expression data from the published literature on psychiatric disorders. Users can search the accumulated data to find the evidence in support of the involvement of a particular genomic region with a set of important psychiatric disorders, ADHD, autism, bipolar disorder, eating disorder, major depressive disorder, schizophrenia, and smoking behavior. It contains findings from manual reviews of 144 papers in psychiatric genetics, 136 primary reports and 8 meta-analyses. Disorders covered include schizophrenia (44 papers), autism (24 papers), bipolar disorder (24 papers), smoking behavior (24 papers), major depressive disorder and neuroticism (14 papers), ADHD (8 papers), eating disorders (3 papers), and a combined schizophrenia-bipolar phenotype (3 papers). The unbiased searches integrated into SLEP include genomewide linkage (117 papers), genomewide association (15 papers), copy number variation (9 papers), and gene expression studies of post-mortem brain tissue (3 meta-analyses courtesy of the Stanley Foundation). In total, SLEP captures 3,741 findings from these 144 papers. SLEP also contains over 70,000 SignPosts. These annotations derive from many different sources and are designed to try to capture current state of knowledge about disease associations in the human genome. SignPosts can be searched simultaneously with the psychiatric genetics literature in order to integrate these two bodies of knowledge. The SignPosts include: accumulated GWAS findings from the human genetics literature, the OMIM database, candidate gene association study literature, CNV location and frequency data, SNPs that influence gene expression in brain, genes expressed in brain, genes with evidence of imprinting and random monoalleleic expression, genes mutated in breast or colorectal cancer, and pathway data from BioCyc.

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• 17 years ago - by Anonymous

The Salk Institute conducts research within three major areas of study: Molecular Biology and Genetics; Neurosciences; and Plant Biology. Six key areas represent strategic research priorities: Chemistry and Proteomics; Stem Cell Biology; Cell Biology; Regulatory Biology; Metabolic Research; and Computational and Theoretical Biology.

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• 16 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. The KTH Research Project Database is intended to contain all the currently on-going projects at KTH. Sponsors: This resource is supported by the Royal Institute of Technology, Sweden,

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• 17 years ago - by Anonymous

This Wiki page provides information about Interactome of various species. An interactome of a species provides an important clues on how to interpret metabolic pathways of constituent enzymes and global protein network, which facilitates in turn to understand the mechanism responsible for the cellular functions.

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• 17 years ago - by Anonymous

Research team focused on research and development of new algorithms in medical imaging, information processing and computer assisted intervention in the context of the pathologies of the central nervous system. Research team jointly affiliated to INSERM (National Institute of Health and Scientific Research), Inria (National Institute of Research in Computer Sciences and Automation) and IRISA / UMR CNRS 6074, University of Rennes I. Multidisciplinary team merging researchers in image processing and medical doctors.

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• 17 years ago - by Anonymous

Bio Resource for array genes is a free online resource for easy access to collective and integrated information from various public biological resources for human, mouse, rat, fly and c. elegans genes. The resource includes information about the genes that are represented in Unigene clusters. This resource provides interactive tools to selectively view, analyze and interpret gene expression patterns against the background of gene and protein functional information. Different query options are provided to mine the biological relationships represented in the underlying database. Search button will take you to the list of query tools available. This Bio resource is a platform designed as an online resource to assist researchers in analyzing results of microarray experiments and developing a biological interpretation of the results. This site is mainly to interpret the unique gene expression patterns found as biological changes that can lead to new diagnostic procedures and drug targets. This interactive site allows users to selectively view a variety of information about gene functions that is stored in an underlying database. Although there are other online resources that provide a comprehensive annotation and summary of genes, this resource differs from these by further enabling researchers to mine biological relationships amongst the genes captured in the database using new query tools. Thus providing a unique way of interpreting the microarray data results based on the knowledge provided for the cellular roles of genes and proteins. A total of six different query tools are provided and each offer different search features, analysis options and different forms of display and visualization of data. The data is collected in relational database from public resources: Unigene, Locus link, OMIM, NCBI dbEST, protein domains from NCBI CDD, Gene Ontology, Pathways (Kegg, Genmapp and Biocarta) and BIND (Protein interactions). Data is dynamically collected and compiled twice a week from public databases. Search options offer capability to organize and cluster genes based on their Interactions in biological pathways, their association with Gene Ontology terms, Tissue/organ specific expression or any other user-chosen functional grouping of genes. A color coding scheme is used to highlight differential gene expression patterns against a background of gene functional information. Concept hierarchies (Anatomy and Diseases) of MESH (Medical Subject Heading) terms are used to organize and display the data related to Tissue specific expression and Diseases. Sponsors: BioRag database is maintained by the Bioinformatics group at Arizona Cancer Center. The material presented here is compiled from different public databases. BioRag is hosted by the Biotechnology Computing Facility of the University of Arizona. 2002,2003 University of Arizona.

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• 17 years ago - by Anonymous

A software application and database viewing system for genomic research, more specifically formulti-genome comparison and pattern discovery via genome self-comparison. Data are available for a range of species including Human Chr3, Human Chr12, Sea Urchin, Tribolium, and cow. The Genboree Discovery System is the largest software system developed at the bioinformatics laboratory at Baylor in close collaboration with the Human Genome Sequencing Center. Genboree is a turnkey software system for genomic research. Genboree is hosted on the Internet and, as of early 2007, the number of registered users exceeds 600. While it can be configured to support almost any genome-centric discovery process, a number of configurations already exist for specific applications. Current focus is on enabling studies of genome variation, including array CGH studies, PCR-based resequencing, genome resequencing using comparative sequence assembly, genome remapping using paired-end tags and sequences, genome analysis and annotation, multi-genome comparison and pattern discovery via genome self-comparison. Genboree database and visualization settings, tools, and user roles are configurable to fit the needs of specific discovery processes. Private permanent project-specific databases can be accessed in a controlled way by collaborators via the Internet. Project-specific data is integrated with relevant data from public sources such as genome browsers and genomic databases. Data processing tools are integrated using a plug-in model. Genboree is extensible via flexible data-exchange formats to accommodate project specific tools and processing steps. Our Positional Hashing method, implemented in the Pash program, enables extremely fast and accurate sequence comparison and pattern discovery by employing low-level parallelism. Pash enables fast and sensitive detection of orthologous regions across mammalian genomes, and fast anchoring of hundreds of millions of short sequences produced by next-generation sequencing technologies. We are further developing the Pash program and employing it in the context of various discovery pipelines. Our laboratory participates in the pilot stage of the TCGA (The Cancer Genome Atlas) project. We aim to develop comprehensive, rapid, and economical methods for detecting recurrent chromosomal aberrations in cancer using next-generation sequencing technologies. The methods will allow detection of recurrent chromosomal aberrations in hundreds of small (

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• 17 years ago - by Anonymous