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A database of proteins identified by various 2-D PAGE and SDS-PAGE reference maps. Each SWISS-2DPAGE entry contains textual data on one protein, including mapping procedures, physiological and pathological information, experimental data (isoelectric point, molecular weight, amino acid composition, peptide masses) and bibliographical references. In addition to this textual data, SWISS-2DPAGE provides several 2-D PAGE and SDS-PAGE images showing the experimentally determined location of the protein, as well as a theoretical region computed from the sequence protein, indicating where the protein might be found in the gel. Using the database, users can locate these proteins on the 2-D PAGE maps or display the region of a 2-D PAGE map where one might expect to find a protein from UniProtKB/Swiss-Prot.

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• SciCrunch
• 17 years ago - by Anonymous

A basic ontology which describes the proteomics pipeline infrastructure for CPTAC project

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• SciCrunch
• 13 years ago - by Anonymous

Open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions. Direct user submissions of molecular interaction data are encouraged, which may be deposited prior to publication in a peer-reviewed journal. The IntAct Database contains (Jun. 2014): * 447368 Interactions * 33021 experiments * 12698 publications * 82745 Interactors IntAct provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows "zooming in" on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available.

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• SciCrunch
• 17 years ago - by Anonymous

Web-based tool for the ontological analysis of large lists of genes. It can be used to determine biological annotations or combinations of annotations that are significantly associated to a list of genes under study with respect to a reference list. As well as single annotations, this tool allows users to simultaneously evaluate annotations from different sources, for example Biological Process and Cellular Component categories of Gene Ontology., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 15 years ago - by Anonymous

Project to map the neural pathways that underlie human brain function for several modalities of neuroimaging data including fMRI. The purpose of the Project is to acquire and share data about the structural and functional connectivity of the human brain. It will greatly advance the capabilities for imaging and analyzing brain connections, resulting in improved sensitivity, resolution, and utility, thereby accelerating progress in the emerging field of human connectomics. Altogether, the Human Connectome Project will lead to major advances in the understanding of what makes us uniquely human and will set the stage for future studies of abnormal brain circuits in many neurological and psychiatric disorders. The sixteen institutes and centers of the NIH Blueprint for Neuroscience have funded two major grants that will take complementary approaches to deciphering the brain's amazingly complex wiring diagram. An 11-institution consortium led by Washington University in St. Louis and the University of Minnesota received a 5-year grant to enable development and utilization of advanced Magnetic Resonance Imaging (MRI) methods to chart brain circuitry. A consortium led by Massachusetts General Hospital and the University of California at Los Angeles received a grant to enable building and refining a next-generation 3T MR scanner that improves the quality and spatial resolution with which brain connectivity data can be acquired at this field strength.

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• SciCrunch
• 15 years ago - by Anonymous

Collection of tools developed by GO Consortium and by third parties. Tools are listed by category or alphabetically and continue to be improved and expanded.

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• SciCrunch
• 15 years ago - by Anonymous

Pharmacology research teams and faculty study mechanisms of disease, develop and test novel drug therapies and seek to understand and prevent drug interactions. They also educate and train medical students, graduate students, residents and fellows in field of pharmacology.

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• SciCrunch
• 15 years ago - by Anonymous

This genomic tRNA database contains tRNA gene predictions made by the program tRNAscan-SE (Lowe & Eddy, Nucl Acids Res 25: 955-964, 1997) on complete or nearly complete genomes. Unless otherwise noted, all annotation is automated, and has not been inspected for agreement with published literature. Transfer RNAs (tRNAs) represent the single largest, best-understood class of non-protein coding RNA genes found in all living organisms. By far, the major source of new tRNAs is computational identification of genes within newly sequenced genomes. To organize the rapidly growing collection and enable systematic analyses, we created the Genomic tRNA Database (GtRNAdb). The web resource provides overview statistics of tRNA genes within each analyzed genome, including information by isotype and genetic locus, easily downloadable primary sequences, graphical secondary structures and multiple sequence alignments. Direct links for each gene to UCSC eukaryotic and microbial genome browsers provide graphical display of tRNA genes in the context of all other local genetic information. The database can be searched by primary sequence similarity, tRNA characteristics or phylogenetic group. Inevitably with automated sequence analysis, we find exceptions to general identification rules, isoacceptor type predictions (esp. due to variable post-transcriptional anticodon modification), and questionable tRNA identifications (due to pseudogenes, SINES, or other tRNA-derived elements). We attempt to document all cases we come across, and welcome feedback on new or unrecognized discrepancies.

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• SciCrunch
• 15 years ago - by Anonymous

The SZGene database provides a comprehensive, unbiased and regularly updated field synopsis of genetic association studies performed in schizophrenia. In addition, hundreds of up-to-date meta-analyses are available for all eligible polymorphisms with sufficient data. Eligible publications are identified following systematic searches of scientific literature databases, as well as the table of contents of journals in genetics and psychiatry. The database can be searched either by a variety of dropdown menus or by specific keywords. For each gene, summary overviews are provided displaying key characteristics for each publication, including links to genotype distributions of the polymorphisms studied, random-effects allelic meta-analyses, and funnel plots for an assessment of publication bias.

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• SciCrunch
• 17 years ago - by Anonymous

Genetic factors contribute significantly to ASD. AutismKB is an evidence-based knowledgebase of Autism spectrum disorder (ASD) genetics. The current version contains 2193 genes (99 syndromic autism related genes and 2135 non-syndromic autism related genes), 4617 Copy Number Variations (CNVs) and 158 linkage regions associated with ASD by one or more of the following six experimental methods: # Genome-Wide Association Studies (GWAS); # Genome-wide CNV studies; # Linkage analysis; # Low-scale genetic association studies; # Expression profiling; # Other low-scale gene studies. Based on a scoring and ranking system, 99 syndromic autism related genes and 383 non-syndromic autism related genes (434 genes in total) were designated as having high confidence. Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder with a prevalence of 1.0-2.6%. The three core symptoms of ASD are: # impairments in reciprocal social interaction; # communication impairments; # presence of restricted, repetitive and stereotyped patterns of behavior, interests and activities.

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• SciCrunch
• 15 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 26, 2016. The T-DB contains millions of structural alignments between all proteins in the PDB as of July 2005 found by the TOPOFIT method. Structural neighbors to the query protein structure can be retrieved by the PDB code and chain id. Pairwise or multiple structural alignments can be visualized in 3D with the FRIEND software. In the TOPOFIT method, similarity of protein structures is analyzed using three-dimensional Delaunay triangulation patterns derived from backbone representation. It has been found that structurally related proteins have a common spatial invariant part, a set of tetrahedrons, mathematically described as a common spatial sub-graph volume of the three-dimensional contact graph derived from Delaunay tessellation (DT). Based on this property of protein structures we present a novel common volume superimposition (TOPOFIT) method to produce structural alignments of proteins. The superimposition of the DT patterns allows one to uniquely identify a common number of equivalent residues in the structural alignment, in other words, TOPOFIT identifies a feature point on the RMSD/Ne curve, a topomax point, until which two structures correspond to each other including backbone and inter-residue contacts, while the growing number of mismatches between the DT patterns occurs at larger RMSD (Ne) after topomax point. The topomax point is present in all alignments from different protein structural classes; therefore, the TOPOFIT method identifies common, invariant structural parts between proteins. The TOPOFIT method adds new opportunities for the comparative analysis of protein structures and for more detailed studies on understanding the molecular principles of tertiary structure organization and functionality. It helps to detect conformational changes, topological differences in variable parts, which are particularly important for studies of variations in active/binding sites and protein classification.

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• SciCrunch
• 17 years ago - by Anonymous

Open source software system for capturing, storing and analyzing raw phenotyping data from SOPs contained in EMPReSS, it provides access to raw and annotated mouse phenotyping data generated from primary pipelines such as EMPReSSlim and secondary procedures from specialist centers. Mutants of interest can be identified by searching the gene or the predicted phenotype. You can also access phenotype data from the EMPReSSlim Pipeline for inbred mouse strains. Initially EuroPhenome was developed within the EUMORPHIA programme to capture and store pilot phenotyping data obtained on four background strains (C57BL/6J, C3H/HeBFeJ, BALB/cByJ and 129/SvPas). EUMORPHIA (European Union Mouse Research for Public Health and Industrial Applications) was a large project comprising of 18 research centers in 8 European countries, with the main focus of the project being the development of novel approaches in phenotyping, mutagenesis and informatics to improve the characterization of mouse models for understanding human molecular physiology and pathology. The current version of EuroPhenome is capturing data from the EUMODIC project as well as the WTSI MGP, HMGU GMC pipeline and the CMHD. EUMODIC is undertaking a primary phenotype assessment of up to 500 mouse mutant lines derived from ES cells developed in the EUCOMM project as well as other lines. Lines showing an interesting phenotype will be subject to a more in depth assessment. EUMODIC is building upon the comprehensive database of standardized phenotyping protocols, called EMPReSS, developed by the EUMORPHIA project. EUMODIC has developed a selection of these screens, called EMPReSSslim, to enable comprehensive, high throughput, primary phenotyping of large numbers of mice. Phenovariants are annotated using a automated pipeline, which assigns a MP term if the mutant data is statistically different to the baseline data. This data is shown in the Phenomap and the mine for a mutant tool. Please note that a statistically significant result and the subsequent MP annotation does not necessarily mean a true phenovariant. There are other factors that could cause this result that have not been accounted for in the analysis. It is the responsibility of the user to download the data and use their expert knowledge or further analysis to decide whether they agree or not. EuroPhenome is primarily based in the bioinformatics group at MRC Harwell. The development of EuroPhenome is in collaboration with the Helmholtz Zentrum Munchen, Germany, the Wellcome Trust Sanger Institute, UK and the Institut Clinique de la Souris, France.

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• SciCrunch
• 17 years ago - by Anonymous

A web-based, interactive brain atlas viewer, containing a growing number of atlas templates for various species, including mouse, macaque and human. Standard features include fast brain region lookup, point and click to select a region and view its full 3D extent, mark a stereotaxic coordinate and view all regions in a hierarchy. Built-in extensions are the CoCoMac plugin, which provides a spatial display of Macaque connectivity, and a service to transform stereotaxic coordinates to and from the INCF Waxholm space for the mouse. Three dimensional renderings of brain regions are available through a Matlab interface (local installation of Matlab required). The SBA is designed to be customizable. External users can create plugins, hosted on their own servers, to interactively attach images or data to spatial atlas locations. This fully web-based display engine for brain atlases and topologies allows client websites to show brain region related data in a 3D interactive context. Currently available atlases are: * Macaque: The Paxinos Rhesus Monkey atlas (2000) * Macaque: Various templates available through Caret, registered to F99 space: Felleman and Van Essen (1991), Lewis and Van Essen (2000), Regional Map from K��tter and Wanke (2005), Paxinos Rhesus Monkey (2000) * Macaque: The NeuroMaps Macaque atlas (2008) * Mouse: The INCF Waxholm Space for the mouse (2011). Previous versions available. * Mouse: The Allen Mouse Brain volumetric atlas (ABA07) * Human: The LPBA40 parcellation, registered to SRI24 space A variety of services are being developed around the templates contained in the Scalable Brain Atlas. For example, you can include thumbnails of brain regions in your own webpage. Other applications include: * Analyze atlas templates in Matlab * List all regions belonging to the given template * List of supported atlas templates * Find region by coordinate * Color-coded PNG (bitmap) or SVG (vector) image of a brain atlas slice * Region thumbnail in 2D (slice) or 3D (stack of slices) The Scalable Brain Atlas is created by Rembrandt Bakker and Gleb Bezgin, under supervision of Rolf K��tter in the NeuroPhysiology and -Informatics group of the Donders Institute, Radboud UMC Nijmegen.

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• SciCrunch
• 16 years ago - by Anonymous

Accepts and provides access to biogeographic data collected throughout the global oceans. The datasets are integrated so you can search them all seamlessly by species name, higher taxonomic level, geographic area, depth, and time; and then map and find environmental data related to the locations. Created by the Census of Marine Life, OBIS is now part of the Intergovernmental Oceanographic Commission (IOC) of UNESCO, under its International Oceanographic Data and Information Exchange (IODE) programme

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• SciCrunch
• 14 years ago - by Anonymous

A database for aligned ribosomal complexes that provides a resource for directly comparing the structures. A collection of files deposited in the RCSB protein data bank and the Electron Microscopy Data Bank have been aligned so as to make direct comparison of the structures possible. An easy-to-use, searchable interface allows users to access and download >130 cryo-EM maps and >300 atomic models in the format of brix and pdb files, respectively. The aligned coordinate system substantially simplifies direct visualization of conformational changes in the ribosome, such as subunit rotation and head-swiveling, as well as direct comparison of bound ligands, such as antibiotics or translation factors.

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• SciCrunch
• 15 years ago - by Anonymous

IMGT/LIGM-DB is a comprehensive database of immunoglobulin (IG) and T cell receptor (TR) nucleotide sequences from human and other vertebrate species (270). IMGT/LIGM-DB includes all germline (non-rearranged) and rearranged IG and TR genomic DNA (gDNA) and complementary DNA (cDNA) sequences published in generalist databases. IMGT/LIGM-DB allows searches from the Web interface according to biological and immunogenetic criteria through five distinct modules depending on the user interest. Users can search the catalogue by accession number, mnemonic, definition, creation date, length, or annotation level. They also have the option to search through taxonomic classification, keywords, and annotated labels. For a given entry, nine types of display are available including the IMGT flat file, the translation of the coding regions and the analysis by the IMGT/V-QUEST tool (see parent org. below). IMGT/LIGM-DB distributes expertly annotated sequences. The annotations hugely enhance the quality and the accuracy of the distributed detailed information. They include the sequence identification, the gene and allele classification, the constitutive and specific motif description, the codon and amino acid numbering, and the sequence obtaining information, according to the main concepts of IMGT-ONTOLOGY. They represent the main source of IG and TR gene and allele knowledge stored in IMGT/GENE-DB and in the IMGT reference directory., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 17 years ago - by Anonymous

A database of sequence alignments and phylogenetic trees for chordates and embryophytes. The Adaptive Evolution Database (TAED) was first presented as a collection of branches from chordate and embryophyte gene families with fast evolutionary rates mapped onto the NCBI taxonomy (1,2). The original gene families were from the Master Catalog and are proprietary (3). A new version of TAED is now presented as a taxonomic shell together with a gene family database. In addition to multiple sequence alignments and phylogenetic trees for all families of chordate and embryophyte sequences, the ratio of non-synonymous to synonymous nucleotide substitution rates (Ka/Ks) is provided for each branch of every phylogenetic tree. This ratio, when significantly greater than 1, is an indicator of positive selection and potentially a change of function of the encoded protein. With a gene tree to species tree mapping, the branches significantly greater than 1 are collated together in a phylogenetic context. The framework is expandable to incorporate other genomic-scale information in a phylogenetic context. Ultimately, the database is designed both to provide high-quality gene families with multiple sequence alignments and phylogenetic trees for chordates and embryophytes, and to enable asking the question, What makes each species unique at the molecular genomic level?

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• SciCrunch
• 17 years ago - by Anonymous

Program that develops materials and methods to improve measurements of autoantibodies that are predictive of type 1 diabetes. These are the most sensitive and meaningful measures for predicting this disease. Historically, autoantibody measures have been variable among laboratories; therefore, this program, in collaboration with the Immunology of Diabetes Society, was established. The goals of DASP are to improve laboratory methods, evaluate laboratory performance, support the development of sensitive and specific measurement technologies, and develop reference methods. Currently, 48 key laboratories from 19 countries participate in DASP.

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• dkNET
• 14 years ago - by Anonymous

An information resource of Arabidopsis promoter sequences, transcription factors and their target genes that contains three databases. *AtcisDB consists of approximately 33,000 upstream regions of annotated Arabidopsis genes (TAIR9 release) with a description of experimentally validated and predicted cis-regulatory elements. *AtTFDB contains information on approximately 1,770 transcription factors (TFs). These TFs are grouped into 50 families, based on the presence of conserved domains. *AtRegNet contains 11,355 direct interactions between TFs and target genes. They provide free download of Arabidopsis thaliana cis-regulatory database (AtcisDB) and transcription factor database (AtTFDB).

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• SciCrunch
• 17 years ago - by Anonymous

It is a Brazilian face database that contains a set of face images taken between June 2005 and March 2006 at the Artificial Intelligence Laboratory of FEI in So Bernardo do Campo, So Paulo, Brazil. There are 14 images for each of 200 individuals, a total of 2800 images. All images are colourful and taken against a white homogenous background in an upright frontal position with profile rotation of up to about 180 degrees. Scale might vary about 10 and the original size of each image is 640x480 pixels. All faces are mainly represented by students and staff at FEI, between 19 and 40 years old with distinct appearance, hairstyle, and adorns. The number of male and female subjects are exactly the same and equal to 100. Figure 1 shows some examples of image variations from the FEI face database. In addition, we provide a subset of the FEI face database composed of only frontal face images previously aligned to a common template so that the pixel-wise features extracted from the images correspond roughly to the same location across all subjects. In this manual alignment, we have randomly chosen the frontal image of a subject as template and the directions of the eyes and nose as a location reference. All these frontal images were then cropped to the size of 360x260 pixels. Since the number of subjects is equal to 200 and each subject has two frontal images (one with a neutral or non-smiling expression and the other with a smiling facial expression), there are 400 full frontal face images manually registered to evaluate experiments on a controlled environment. More recently, with the support of CNPq under the grant 472386/2007-7, we have proposed and implemented a sequence of image processing steps to automatically normalize frontal face images. A computational tool has been developed to minimize image variations due to the acquisition protocol. Figure 2 shows the average face images of the neutral (left) and smiling (right) facial expressions before and after the normalization. We believe that this additional set of frontal face images is particularly useful for evaluating experiments on synthesizing realistic expressions and aging estimation in 2D face data sets.

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• SciCrunch
• 14 years ago - by Anonymous