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http://www.broad.mit.edu/node/305
The Connectivity Map aims to generate a detailed map that links gene patterns associated with disease to corresponding patterns produced by drug candidates and a variety of genetic manipulations. The Connectivity Map is the most comprehensive effort yet for using genomics in a drug-discovery framework. It allows researchers to screen compounds against genome-wide disease signatures, rather than a pre-selected set of target genes. Drugs are paired with diseases using sophisticated pattern-matching methods with a high level of resolution and specificity. To build a Connectivity Map, the Broad Institute brings together molecular biologists, genomics specialists, computational scientists, pharmacologists, chemists and chemical biologists, as well as expertise from across the breadth and depth of medicine.Connectivity map is a large public database of signatures of drugs and genes, and pattern-matching tools to detect similarities among these signatures.The parent site for the Broad Institute at MIT has a software library of software applications developed for use in genetic analysis.
Proper citation: National Institute of Mental Health (NIMH) Human Genetics Initiative (RRID:SCR_007436) Copy
Repository of mouse vectors, ES cells, mice, embryos, and sperm generated by NIH KOMP Mutagenesis Project. In addition, KOMP Repository offers services in support of KOMP products, including ES cell microinjection, vector cloning, post-insertional modification of cloned ES cells, cryopreservation, assisted reproduction techniques (IVF, ICSI) and mouse breeding, pathology services, phenotyping services, etc. KOMP Repository is final component of more than $50 million trans-NIH initiative to increase availability of genetically altered mice and related materials. The University of California, Davis (UC Davis) and Children''s Hospital Oakland Research Institute (CHORI) in Oakland, Calif., are collaborating to preserve, protect, and make available about 8,500 types of knockout mice and related products available to research community. Products are generated by two KOMP mutagenesis teams (CSD consortium and Regeneron Inc). All KOMP products generated by CSD consortium and Regeneron are available through KOMP Repository. Notice as of December 19, 2019: Materials from KOMP Repository have been deposited into MMRRC, including all mouse models and mouse embryonic stem cell lines. Eventually www.komp.org will be sunsetting, and IMSR will remove KOMP Repository listings, since they were double listed in MMRRC. MMRRC will contain the most accurate and up to date resource models.
Proper citation: Knockout Mouse Project Repository (RRID:SCR_007318) Copy
http://www.geisha.arizona.edu/geisha/
Online repository for chicken in situ hybridization information. This site presents whole mount in situ hybridization images and corresponding probe and genomic information for genes expressed in chicken embryos in Hamburger Hamilton stages 1-25 (0.5-5 days). The GEISHA project began in 1998 to investigate using high throughput whole mount in situ hybridization to identify novel, differentially expressed genes in chicken embryos. An initial expression screen of approximately 900 genes demonstrated feasibility of the approach, and also highlighted the need for a centralized repository of in situ hybridization expression data. Objectives: The goals of the GEISHA project are to obtain whole mount in situ hybridization expression information for all differentially expressed genes in the chicken embryo between HH stages 1-25, to integrate expression data with the chicken genome browsers, and to offer this information through a user-friendly graphical user interface. In situ hybridization images are obtained from three sources: 1. In house high throughput in situ hybridization screening: cDNAs obtained from several embryonic cDNA libraries or from EST repositories are screened for expression using high throughput in situ hybridization approaches. 2. Literature curation: Agreements with journals permit posting of published in situ hybridization images and related information on the GEISHA site. 3. Unpublished in situ hybridization information from other laboratories: laboratories generally publish only a small fraction of their in situ hybridization data. High quality images for which probe identity can be verified are welcome additions to GEISHA.
Proper citation: GEISHA - Gallus Expression in Situ Hybridization Analysis: A Chicken Embryo Gene Expression Database (RRID:SCR_007440) Copy
http://senselab.med.yale.edu/ordb/
Database of vertebrate olfactory receptors genes and proteins. It supports sequencing and analysis of these receptors by providing a comprehensive archive with search tools for this expanding family. The database also incorporates a broad range of chemosensory genes and proteins, including the taste papilla receptors (TPRs), vomeronasal organ receptors (VNRs), insect olfaction receptors (IORs), Caenorhabditis elegans chemosensory receptors (CeCRs), and fungal pheromone receptors (FPRs). ORDB currently houses chemosensory receptors for more than 50 organisms. ORDB contains public and private sections which provide tools for investigators to analyze the functions of these very large gene families of G protein-coupled receptors. It also provides links to a local cluster of databases of related information in SenseLab, and to other relevant databases worldwide. The database aims to house all of the known olfactory receptor and chemoreceptor sequences in both nucleotide and amino acid form and serves four main purposes: * It is a repository of olfactory receptor sequences. * It provides tools for sequence analysis. * It supports similarity searches (screens) which reduces duplicate work. * It provides links to other types of receptor information, e.g. 3D models. The database is accessible to two classes of users: * General public www users have full access to all the public sequences, models and resources in the database. * Source laboratories are the laboratories that clone olfactory receptors and submit sequences in the private or public database. They can search any sequence they deposited to the database against any private or public sequence in the database. This user level is suited for laboratories that are actively cloning olfactory receptors.
Proper citation: Olfactory Receptor DataBase (RRID:SCR_007830) Copy
http://genomics.senescence.info/
Collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses. A major resource in HAGR is GenAge, which includes a curated database of genes related to human aging and a database of ageing- and longevity-associated genes in model organisms. Another major database in HAGR is AnAge. Featuring over 4,000 species, AnAge provides a compilation of data on aging, longevity, and life history that is ideal for the comparative biology of aging. GenDR is a database of genes associated with dietary restriction based on genetic manipulation experiments and gene expression profiling. Other projects include evolutionary studies, genome sequencing, cancer genomics, and gene expression analyses. The latter allowed them to identify a set of genes commonly altered during mammalian aging which represents a conserved molecular signature of aging. Software, namely in the form of scripts for Perl and SPSS, is made available for users to perform a variety of bioinformatic analyses potentially relevant for studying aging. The Perl toolkit, entitled the Ageing Research Computational Tools (ARCT), provides modules for parsing files, data-mining, searching and downloading data from the Internet, etc. Also available is an SPSS script that can be used to determine the demographic rate of aging for a given population. An extensive list of links regarding computational biology, genomics, gerontology, and comparative biology is also available.
Proper citation: Human Ageing Genomic Resources (RRID:SCR_007700) Copy
http://flybrain.neurobio.arizona.edu/
An interactive database of the Drosophila melanogaster nervous system. It is used by the drosophila neuroscience community and by other researchers studying arthropod brain structure. Flybrain contains neuroanatomical peer reviewed descriptions of the central and peripheral nervous system of Drosophila melanogaster. It also contains an introductory hypertext tour guide to the basic structure of the nervous system, as well as more specific information concerning different anatomical structures, developmental stages, and visualization techniques for the Drosophila nervous system. Additionally, The site contains schematic representations, a 3D project, immunocytology stains, a library of golgi impregnations, and enhancer-trap images.
Proper citation: MIRROR: FlyBrain, An Online Atlas and Database of the Drosophila Nervous System (RRID:SCR_007661) Copy
http://claire.bardel.free.fr/software.html
Software package to perform phylogeny based association and localization analysis.Used for association detection and localization of susceptibility sites using haplotype phylogenetic trees. Performs these two phylogeny-based analysis: tests association between candidate gene and disease; pinpoints markers (SNPs) that are putative disease susceptibility loci.
Proper citation: ALTree (RRID:SCR_007562) Copy
http://organelledb.lsi.umich.edu/
Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light.
Proper citation: Organelle DB (RRID:SCR_007837) Copy
Database of gene expression in whole-mount mouse embryos derived from in situ hybridization on mid-gestation mouse embryos. A genome wide screening for genes showing a tissue restricted expression pattern in mid-gestation embryos is performed to identify genes that are likely to play an important role in the regulatory networks controlling pattern formation and organogenesis. The screening provides the basis for imaging the molecular anatomy of the mouse embryo, and for creating a gene resource for a directed functional analysis of developmental processes. The experimental protocol is available. Pattern genes in MAMEP: 1912 Images in MAMEP: 23994
Proper citation: MAMEP - Molecular Anatomy of the Mouse Embryo Project (RRID:SCR_007768) Copy
The Bio-Lab is a Bioengineering and Bioimages laboratory and it''s part of DIST (Department of Computer Science, Control Systems and Telecommunications- University of Genoa). The main research activities of the Bioengineering Laboratory are related with the acquisition, processing and rendering of bioimages with the aim of exploring the links between structure and functionality of biological systems (images of cells in optical confocal microscopy) and for diagnostic and therapeutical processes (images of the human body in Magnetic Resonance, Computerized X-ray Tomography, ultrasounds and other modalities). The main research activities of the laboratory are related to: - Bioimages: medical/biological image analysis and visualization methods are investigated, with a deep attention to the applications development for the driven therapy. - Bioinformatics: in this field, advanced technologies and knowledge related to production and treatment of gene expression microarray distributed data have been implemented. - Tissue Engineering: this research activity is addressed to the development and testing of biomaterials, coupled with adult stem cells for the in vivo bone formation. - Neuroinformatics: the interaction between results of functional neuroimaging and brain computational models has been studied. Among the equipment of the Bioengineering Laboratory there are of particular interest: 2D-3D cell culture bioreactor systems and a virtual reality platform for the interaction person-bioimages, medical data and 3D models. The Bio-Lab also manages a GRID node belonging to the international GILDA network, which is built by 6 server, for a total amount of 12 CPU, 7 GB RAM and 500 GB Disk Space. Additionally, the confocal laser is a very essential tool in this lab; it is a scanning optical microscope with a hardware/software framework virtual reality-like for the interaction person-bioimages, with stereovision, and equipment for head tracking and pointing. The Bio-Lab collaborates with several research institutes and centers, such as the National Institute of Nuclear Physics, the National Research Council, and the Advanced Biotechnology Center (visit Research area or Project area in the web site). Promising collaborations are also on going with different technological companies in the national scenario. The laboratory has also been involved in several international and national projects funded by the European Commission and MUR. Specifically, it is involved in several projects funded by the European Commission projects related to the area of Health Care Telematics, with special reference to emergency telemedicine.
Proper citation: biolab - Bioengineering and Bioimages Laboratory (RRID:SCR_008029) Copy
An animated primer on the basics of DNA, genes, and heredity organized around three key concepts: Classical Genetics, Molecules of Genetics, and Genetic Organization and Control. The science behind each concept is explained by: animation, image gallery, video interviews, problem, biographies, and links.
Proper citation: DNA From The Beginning: AN Animated Primer on the Basics of DNA, Genes, and Heredity (RRID:SCR_008028) Copy
http://locus.jouy.inra.fr/cgi-bin/bovmap/intro.pl
THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database containing information on the cattle genome comprising loci list, phenes list, homology query, cattle maps, gene list, and chromosome homology. The objective of BovMap is to develop a set of anchored loci for the cattle genome map. In total, 58 clones were hybridized with chromosomes and identified loci on 22 of the 31 different bovine chromosomes. Three clones contained satellite DNA. Two or more markers were placed on 12 chromosomes. Sequencing of the microsatellites and flanking regions was performed directly from 43 cosmids, as previously reported. Primers were developed for 39 markers and used to describe the polymorphism associated with the corresponding loci. Users are also allowed to summit their own data for Bovmap. An integrated cytogenetic and meiotic map of the bovine genome has also been developed around the Bovmap database. One objective that Bovmap uses as the mapping strategy for the bovine genome uses large insert clones as a tool for physical mapping and as a source of highly polymorphic microsatellites for genetic typing.
Proper citation: BovMap Database (RRID:SCR_008145) Copy
The E. coli Genome Project has the goal of completely sequencing the E. coli and human genomes. They began isolation of an overlapping lambda clonebank of E. coli K-12 strain MG1655. Those clones served as the starting material in our initial efforts to sequence the whole genome. Improvements in sequencing technology have since reached the point where whole-genome sequencing of microbial genomes is routine, and the human genome has in fact been completed. They initiated additional sequencing efforts, concentrating on pathogenic members of the family Enterobacteriaceae -- to which E. coli belongs. They also began a systematic functional characterization of E. coli K-12 genes and their regulation, using the whole genome sequence to address how the over 4000 genes of this organism act together to enable its survival in a wide range of environments.
Proper citation: E. coli Genome project (RRID:SCR_008139) Copy
A portal to the Mouse Atlas of Gene Expression Project and Dissecting Gene Expression Networks in Mammalian Organogenesis Project. This Atlas will define the normal state for many tissues by determining, in a comprehensive and quantitative fashion, the number and identity of genes expressed throughout development. The resource will be comprehensive, quantitative, and publicly accessible, containing data on essentially all genes expressed throughout select stages of mouse development. Serial Analysis of Gene Expression (SAGE) is the gene expression methodology of choice for this work. Unlike expressed sequence tags (ESTs) and gene chip data, SAGE data are independent of prior gene discovery and are quantitative. Furthermore, SAGE data are digital, easily exchanged between laboratories for comparison and can be added to by scientists for years to come. Thus, this Atlas will include a data structure and data curation strategy that will facilitate the ongoing collection of gene expression data, even after the completion of this project. The Mouse Atlas project compromises 202 SAGE Libraries from 198 tissues. The list of libraries is available in a number of different groupings, including groups of libraries taken from specific tissue locations and libraries taken from specific developmental stages. Furthermore, this atlas will assemble gene expression profiles for a few focused experiments that will test hypotheses related to the techniques employed, tumor models and models of abnormal development. This will test the resource and provide quality control, validation and demonstrate applicability. Additionally, The Mammalian Organogenesis - Regulation by Gene Expression Networks (MORGEN) project will provide a complete, permanent, and accurate picture of mouse gene expression in the heart (atrioventricular canal and outflow tract), pancreas, and liver; new techniques to understand the interplay of proteins governing the expression of genes key to the development of these organ systems; and the identification of the master regulatory switches that control development of the tissues.
Proper citation: Mouse Gene Expression at the BC Cancer Agency (RRID:SCR_008091) Copy
http://www.koki.hu/main.php?folderID=903
The aim of this laboratory is to understand how information is encoded in specific spatiotemporal activity patterns and structural configurations at the circuit, cellular, and molecular levels in the hippocampus, thereby enabling the process of memory. A major task is to find the neuronal codes of internal representations of memory items and the mapping rules between the levels of gene expression/proteins synthesis and the level of cognitive processing. Novel combinations of approaches, including multiple single-cell recording technology, patch-clamp electrophysiology, neuroanatomy/neurochemistry at the cellular and subcellular levels, and computational models are employed to test specific hypotheses about that mapping process (such as local circuit anatomy and activity-dependent short-term and long-term synaptic plasticity). Collaborations within the Institute allows the group to also incorporate gene targeting methods and behavioral learning/memory tests in their methodological repertoire. The laboratory has been focusing on the normal and pathological (epileptic, ischemic) activity of cortical networks, with particular attention to the generation of behaviour-dependent population discharge patterns (theta and gamma oscillations, hippocampal sharp waves). Anatomical, in vitro and in vivo electrophysiological, pharmacological and molecular techniques and modeling are combined to elucidate the functional roles of inhibitory cell types in the control of population synchrony and synaptic plasticity in the hippocampus, their local and subcortical modulation via selective afferent pathways (GABAergic and cholinergic septal, as well as serotonergic raphe input) and pre- or postsynaptic receptors. An expanding new direction of research is related to the role of endocannabinoid signaling in the activity-dependent modulation of GABAergic and glutamatergic transmission, and its involvement in anxiety-like behavior.
Proper citation: Institute of Experimental Medicine of the Hungarian Academy of Sciences: Laboratory of Cerebral Cortext Reserach (RRID:SCR_008041) Copy
http://compgen.bio.unipd.it/bioinfo/
Welcome to the computational genomics laboratory''s home page. Main research interests: computational biology, bioinformatics and systems biology applied to the study of the mechanisms underlying gene expression regulation. They also develop bioinformatic software aiming at helping the research community solve some problems.
Proper citation: Computational Genomics Laboratory (RRID:SCR_007901) Copy
Gene Expression Atlas is a semantically enriched database of meta-analysis based summary statistics over a curated subset of ArrayExpress Archive, servicing queries for condition-specific gene expression patterns as well as broader exploratory searches for biologically interesting genes/samples. The EBI Gene Expression Atlas Blog discusses ideas, features and problems of creating a large scale meta-analytical atlas of gene expression from publicly available microarray data. Atlas REST API provides all the results available in the main web application in a pragmatic, easy to use form - simple HTTP GET queries as input and either JSON or XML formats as output. Gene Expression Atlas goals: 1. Provision of a statistically robust framework for integration of gene expression experiment results across different platforms at a meta-analytical level 2. A simple interface for identifying strong differential expression candidate genes in conditions of interest 3. Integration of ontologies for high quality annotation of gene and sample attributes 4. Construction of new gene expression summarized views, with a view to analysis of putative signaling pathway targets, discovery of correlated gene expression patterns and the identification of condition/tissue-specific patterns of gene expression.
Proper citation: Gene Expression Atlas (RRID:SCR_007989) Copy
http://www.mf.uni-lj.si/bitola/
An interactive literature-based biomedical discovery support system. The goal of this system is to discover new, potentially meaningful relations between a given starting concept of interest and other concepts, by mining the bibliographic database MEDLINE. To make the system more suitable for disease candidate-gene discovery and to decrease the number of candidate relations, we integrated background knowledge about the chromosomal location of the starting disease as well as the chromosomal location of the candidate genes from resources such as Entrez Gene, HUGO and OMIM. The BITOLA system can also be used as an alternative way of searching the Medline database. The system is available in two versions: closed discovery and open discovery. Closed discovery allows the input of two concepts (Example 1: a disorder and a gene. Example 2: a drug and a side effect) and generates potential explanations of the relationship between two entities. It does this by searching published literature to finds intermediate links. Open discovery allows the input of a single concept, then categories for first-order relatives of that concept, then categories for relatives of those first order concepts. Thus it can link from a disease to related drugs, then to genes related to those drugs and then test if those genes have been mentioned/tested in association with the disease. If the answer is no, then the gene is potentially related yet untested in the literature. Thus the open discovery tool is a nominator of new genes, drugs or neuroscience correlates to be investigated with diseases, disorders, physiological responses or any other phenotype.
Proper citation: BITOLA: Biomedical Discovery Support System (RRID:SCR_008175) Copy
http://mousemutant.jax.org/index.html
Producer and supplier of a collection of mice bearing spontaneous mutations. These mice contribute to a better understanding of the genetic bases of neurological, neuromuscular, sensory, metabolic, skeletal/craniofacial and developmental disorders and conditions such as diabetes, obesity and heart disease.
Proper citation: Mouse Mutant Resource (RRID:SCR_008367) Copy
http://ophid.utoronto.ca/navigator/
A software package for visualizing and analyzing protein-protein interaction networks. NAViGaTOR can query OPHID / I2D - online databases of interaction data - and display networks in 2D or 3D. To improve scalability and performance, NAViGaTOR combines Java with OpenGL to provide a 2D/3D visualization system on multiple hardware platforms. NAViGaTOR also provides analytical capabilities and supports standard import and export formats such as GO and the Proteomics Standards Initiative (PSI). NAViGaTOR can be installed and run on Microsoft Windows, Linux / UNIX, and Mac OS systems. NAViGaTOR is written in Java and uses JOGL (Java bindings for OpenGL) to support scalability, highlighting or suppressing of information, and other advanced graphic approaches.
Proper citation: Network Analysis, Visualization and Graphing TORonto (RRID:SCR_008373) Copy
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