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on page 1 showing 20 out of 334 results

Cite this (5 prime end Serial Analysis of Gene Expression Database, RRID:SCR_001680)

URL: http://5sage.gi.k.u-tokyo.ac.jp/

Resource Type: Resource, data or information resource, database

THIS RESOURCE IS NO LONGER IN SERVICE, documented on October 30, 2012. A database that displays the observed frequencies of individual 5' end SAGE tags and previously unknown transcription start sites in the promoter regions, introns and intergenic regions of known genes. 5'SAGE will be useful for analyzing promoter regions and start site variation in different tissues, and is freely available.

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Cite this (Accelerating Medicines Partnership Autoimmune Diseases of Rheumatoid Arthritis and Lupus, RRID:SCR_003731)

URL: http://www.nih.gov/science/amp/autoimmune.htm

Resource Type: Resource, organization portal, portal, consortium, data or information resource

The autoimmune disease arm of the Accelerating Medicine Partnership (AMP), which aims to identify and validate the most promising biological targets of disease for new diagnostic and drug development, that is focused on rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). They seek to identify shared common flaws in inflammation, particularly those that are shared with a larger number of autoimmune disorders which can cause severe disability, greatly affect quality of life, and are associated with an increased risk of death. This project aims to reveal biomarkers and biological targets for drug development, matching existing drugs to patients with specific molecular profiles who are most likely to benefit. The research plan proposes a 5 year process. Year one will include startup activities such as validation of tissue acquisition processes and analytic technologies, and the development of operating procedures. The second year will focus on identification of disease specific pathways by comparing data from patients and healthy individuals. Years 3-5 will expand the scale to include comparisons of different subsets of patients with RA or lupus to allow molecularly based patient stratification for precise treatment. The final 12 months (2019) will also include preliminary target validation. The data will be made publicly available through an internet-based information portal.

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Cite this (Adult Mouse Anatomy Ontology, RRID:SCR_006568)

URL: http://www.informatics.jax.org/searches/AMA_form.shtml

Resource Type: Resource, ontology, data or information resource, controlled vocabulary

Ontology that organizes anatomical structures for the adult mouse (Theiler stage 28) spatially and functionally, using ''is a'' and ''part of'' relationships. The ontology is used to describe expression data for the adult mouse and phenotype data pertinent to anatomy in standardized ways. The browser can be used to view anatomical terms and their relationships in a hierarchical display.

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Cite this (AffyExpress, RRID:SCR_001321)

URL: http://www.bioconductor.org/packages/release/bioc/html/AffyExpress.html

Resource Type: Resource, software resource

Software package for quality assessment and to identify differentially expressed genes in the Affymetrix gene expression data.

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Cite this (AffyRNADegradation, RRID:SCR_000118)

URL: http://www.bioconductor.org/packages/release/bioc/html/AffyRNADegradation.html

Resource Type: Resource, software resource

Software package that helps with the assessment and correction of RNA degradation effects in Affymetrix 3' expression arrays. The parameter d gives a robust and accurate measure of RNA integrity. The correction removes the probe positional bias, and thus improves comparability of samples that are affected by RNA degradation.

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    aGEM

Cite this (aGEM, RRID:SCR_013349)

URL: http://agem.cnb.csic.es/VisualOmics/aGEM/

Resource Type: Resource, data or information resource, database

Database platform of an integrated view of eight databases (mouse gene expression resources: EMAGE, GXD, GENSAT, BioGPS, ABA, EUREXPRESS; human gene expression databases: HUDSEN, BioGPS and Human Protein Atlas) that allows the experimentalist to retrieve relevant statistical information relating gene expression, anatomical structure (space) and developmental stage (time). Moreover, general biological information from databases such as KEGG, OMIM and MTB is integrated too. It can be queried using gene and anatomical structure. Output information is presented in a friendly format, allowing the user to display expression maps and correlation matrices for a gene or structure during development. An in-depth study of a specific developmental stage is also possible using heatmaps that relate gene expression with anatomical components. This is a powerful tool in the gene expression field that makes easy the access to information related to the anatomical pattern of gene expression in human and mouse, so that it can complement many functional genomics studies. The platform allows the integration of gene expression data with spatial-temporal anatomic data by means of an intuitive and user friendly display.

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Cite this (Allen Brain Atlas API, RRID:SCR_005984)

URL: http://www.brain-map.org/api/index.html

Resource Type: Resource, software resource, software application, source code

API and demo application for accessing the Allen Brain Atlas Mouse Brain data. Data available via the API includes download high resolution images, expression data from a 3D volume, 3D coordinates of the Allen Reference Atlas, and searching genes with similar gene expression profiles using NeuroBlast. Data made available includes: * High resolution images for gene expression, connectivity, and histology experiments, as well as annotated atlas images * 3-D expression summaries registered to a reference space for the Mouse Brain and Developing Mouse Brain * Primary microarray results for the Human Brain and Non-Human Primate * RNA sequencing results for the Developing Human Brain * MRI and DTI files for Human Brain The API consists of the following resources: * RESTful model access * Image download service * 3-D expression summary download service * Differential expression search services * NeuroBlast correlative searches * Image-to-image synchronization service * Structure graph download service

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Cite this (Allen Institute for Brain Science Transgenic Mouse Study, RRID:SCR_002999)

URL: http://transgenicmouse.alleninstitute.org/

Resource Type: Resource, data set, atlas, data or information resource

A comprehensive characterization of expression patterns of genetically-controlled markers or tool genes in the brains of transgenic mice generated by the Allen Institute as well as the broad scientific community. Providing standardized, detailed, anatomical profiling of transgene expression throughout the brain, this dataset is intended to reveal the potential of each transgenic mouse line and help researchers choose the appropriate tools for their studies. Transgenic mice are valuable tools to label selective neuronal or non-neuronal populations, modulate gene expression in these cells or manipulate activity of these cells for the study of neural circuits and brain function. The Allen Institute has launched a project to generate a variety of transgenic mouse lines, mainly using the Cre/lox system, to express fluorescent probes or neuronal activity manipulating tools in a variety of cell types in the brain. At the same time, utilizing Allen Institute's unique high-throughput capability, a pipeline is set up to characterize the ability in directing cell type specific expression in the brains of various transgenic mice generated by the Allen Institute as well as the broad scientific community. Through standardized, detailed, anatomical profiling of the transgene expression in the entire mouse brain, this dataset is intended to provide a comprehensive evaluation of the potential of each transgenic mouse line and help researchers choose the appropriate transgenic tools to study the function of different regions and/or cell types of the brain. This data release adds additional data to the existing set of new Cre-reporter lines generated at the Allen Institute that have stronger expression than other commonly used reporter lines are used to characterize approximately a dozen Cre-driver lines. The types of characterization data include digitized images (of sections sampling the entire brain) of colorimetric in situ hybridization (CISH), double fluorescent in situ hybridization (DFISH), native fluorescence of XFP (generic term for fluorescent proteins of different colors), and immunohistochemical (IHC) labeling of marker genes.

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Cite this (Allen Institute Mouse Diversity Study, RRID:SCR_008009)

URL: http://mousediversity.alleninstitute.org/

Resource Type: Resource, atlas, expression atlas, data or information resource, database

A database, and associated atlas, that characterizes gene expression across genetic backgrounds and sex, expanding beyond the adult male C57BL/6J reference brain comprising the Allen Mouse Brain Atlas to include seven strains of male mice and female C57BL/6J mice. Gene expression was detected using colorimetric RNA in situ hybridization (ISH) that provides cellular level anatomic resolution. ISH data are searchable and organized by gene, strain, or sex.

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Cite this (Allen Reference Atlas, RRID:SCR_013286)

URL: http://mouse.brain-map.org/static/atlas

Resource Type: Resource, atlas, reference atlas, data or information resource

A full-color, high-resolution, Web-based digital brain atlas accompanied by a systematic, hierarchically organized taxonomy of mouse brain structures. The Allen Mouse Brain Atlas and Reference Atlases'' data are obtained, using identical methodology, from 8-week old C57Bl/6J male mouse brain(s) prepared as unfixed, fresh-frozen tissue. The Allen Mouse Brain Reference Atlas was designed to: 1. Allow users to directly compare gene expression patterns to neuroanatomical structures in the Web application 2. Serve as a template for the development of 3D computer graphic models of the mouse brain, providing a foundation for the development of informatics based annotation tools 3. Provide a standard neuroanatomical ontology for determining structural annotation and aid in the construction of a detailed searchable gene expression database. * Coronal Atlas: 132 coronal sections evenly spaced at 100 micrometer intervals and annotated to a detail of numerous brain structures * Sagittal Atlas: 21 representative sagittal sections spaced at 200 micrometer, annotated for 71 major brain regions identified at the top level(s) of the brain structure hierarchical tree * Coronal Legend: Search for a specific structure or browse the coronal reference atlas * Sagittal Legend: Search for a specific structure or browse the sagittal reference atlas The Allen Reference Atlas can also be found in the BioPortal, http://bioportal.bioontology.org/ontologies/40133?p=terms

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Cite this (Alternative Splicing Database, RRID:SCR_007555)

URL: http://www.eurasnet.info/tools/asdatabases

Resource Type: Resource, data or information resource, database

It has been established with the intention of assembling in a central, publicly accessible site information about alternatively spliced genes, their products and expression patterns. Version 2.1 of ASDB consists of two divisions, ASDB(proteins) , which contains amino acid sequences, and ASDB(nucleotides) with genomic sequences.
SWISS-PROT uses two formats for description of alternative splicing Thus the protein sequences were selected from SWISS-PROT using full text search for both the words alternative splicing (usually in the CC lines) and varsplic (in the FT lines). In order to group proteins that could arise by alternative splicing of the same gene, we developed the clustering procedure. Two proteins were linked if they had a common fragment of at least 20 amino acids, and clusters were initially defined as maximum connected groups of linked proteins. It turned out that some clusters were chimeric, in the sense that they contained members of multi-gene families, but not alternatively spliced variants of one gene. Therefore the multiple alignments were subject to additional analysis aimed at detection of chimeric clusters.
Each cluster is represented by multiple alignment of its members constructed using CLUSTALW. The distribution of cluster size, representation of species and other relevant statistics of ASDB(proteins) can be accessed through the links below.
This processing covers the cases when alternatively spliced variants are described in separate SWISS-PROT entries. The other kinds of ASDB records, originating from the SWISS-PROT entries with the varsplic field in the feature table, usually describe the proteins that are not part of any cluster. In these cases, the information on the variable fragments of the several proteins which result from the alternative splicing of a single gene is contained in the entry itself. ASDB(proteins) entries are marked with different symbols to allow for easy differentiation among the three types: those proteins which are part of the ASDB clusters and the corresponding multialignments, those which have the information on different variants in the associated SWISS-PROT entries, and those for which the information on the variants is not available at the present time. ASDB contains internal links between entries and/or clusters, as well as external links to Medline, GenBank and SWISS-PROT entries.
The ASDB(nucleotides) division was generated by collecting all GenBank entries containing the words alternative splicing and further selection of those entries that contain complete gene sequences (all CDS fields are complete, i.e. they do not have continuation signs).
Sponsors: This work was supported by the Director, Office of Energy Research, Office of Biological and Environmental Research, of the US Department of Energy under Contract No. DE-ACO3-76SF00098. Additional support came from grants from the Russian Fund of Basic Research (99-04-48347), the Russian State Scientific Program Human Genome (65/99), and the Merck Genome Research Institute (244).

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Cite this (AmaZonia: Explore the Jungle of Microarrays Results, RRID:SCR_008405)

URL: http://amazonia.montp.inserm.fr/

Resource Type: Resource, data or information resource, database

A web interface and associated tools for easy query of public human transcriptome data by keyword, through thematic pages with list annotations. Amazonia provides a thematic entry to public transcriptomes: users may for instance query a gene on a Stem Cells page, where they will see the expression of their favorite gene across selected microarray experiments related to stem cell biology. This selection of samples can be customized at will among the 6331 samples currently present in the database. Every transcriptome study results in the identification of lists of genes relevant to a given biological condition. In order to include this valuable information in any new query in the Amazonia database, they indicate for each gene in which lists it is included. This is a straightforward and efficient way to synthesize hundreds of microarray publications.

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Cite this (Arabidopsis thaliana Protein Interactome Database, RRID:SCR_001896)

URL: http://www.megabionet.org/atpid/webfile/

Resource Type: Resource, service resource, data or information resource, data repository, storage service resource, database

Centralized platform to depict and integrate the information pertaining to protein-protein interaction networks, domain architecture, ortholog information and GO annotation in the Arabidopsis thaliana proteome. The Protein-protein interaction pairs are predicted by integrating several methods with the Naive Baysian Classifier. All other related information curated is manually extracted from published literature and other resources from some expert biologists. You are welcomed to upload your PPI or subcellular localization information or report data errors. Arabidopsis proteins is annotated with information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways.

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Cite this (ARK-Genomics: Centre for Functional Genomics, RRID:SCR_002214)

URL: http://www.ark-genomics.org/

Resource Type: Resource, organization portal, database, core facility, service resource, portal, access service resource, data or information resource

A high-throughput technology laboratory focused on studies of genome structure and genetic variation, gene expression and gene function, it provides an extensive range of services including: * DNA sequencing of model and non-model genomes using both Next Generation and Sanger sequencing * Gene expression analysis using both microarrays and Next Generation Sequencing * High throughput genotyping of SNP and copy number variants * Data collection and analysis supported in-house high performance computing facilities and expertise * Extensive EST clone collections for a number of animal species * All of the commercially available microarray tools from Affymetrix, Illumina, Agilent and Nimblegen * Parentage testing using microsatellites and smaller SNP panels ARK-Genomics has developed a network of researchers whom they support through each stage of their genomics research, from grant application, experimental design and technology selection, performing wet laboratory protocols, through to the analysis of the data often in conjunction with commercial partners. An important part of the ARK-Genomics service is the opportunity to engage with other scientists and to raise awareness through their training courses, networking events such as their successful conference series.

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Cite this ( Array Information Library Universal Navigator , RRID:SCR_006967)

URL: http://ailun.stanford.edu/

Resource Type: Resource, data analysis service, resource, production service resource, analysis service resource, database, service resource, data or information resource

Re-annotated gene expression / proteomics data from GEO by relating all probe IDs to Entrez Gene IDs once every three months, enabling you to find data from GEO, and compare them from different platforms and species. Platform Annotations adds the latest annotations to any uploaded probe / gene ID list file. Platform Comparison compares any two platforms to find corresponding probes mapping to the same gene. Cross-species mapping maps platform annotations to other species. Gene Search finds deposited platforms and samples in GEO that contain a list of genes. GPL ID Search finds the GPL ID (GEO platform ID) for your array. You can also download the latest annotations files for all arrays and their comprehensive universal gene identifier table, which relates all types of gene / protein / clone identifiers to Entrez Gene IDs for all species. Note: The database was last updated on 4/30/2011. They have successfully mapped 54932732 individual probes from 385099 GEO samples measuring 3519 GEO platforms across 217 species.

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    ASAP

Cite this (ASAP, RRID:SCR_001849)

URL: https://omictools.com/asap-3-tool

Resource Type: Resource, service resource, data or information resource, data repository, storage service resource, database

Database and web interface developed to store, update and distribute genome sequence data and gene expression data. ASAP was designed to facilitate ongoing community annotation of genomes and to grow with genome projects as they move from the preliminary data stage through post-sequencing functional analysis. The ASAP database includes multiple genome sequences at various stages of analysis, and gene expression data from preliminary experiments. Use of some of this preliminary data is conditional, and it is the users responsibility to read the data release policy and to verify that any use of specific data obtained through ASAP is consistent with this policy. There are four main routes to viewing the information in ASAP: # a summary page, # a form to query the genome annotations, # a form to query strain collections, and # a form to query the experimental data. Navigational buttons appear on every page allowing users to jump to any of these four points.

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Cite this (Ascidian Network for InSitu Expression and Embryological Data, RRID:SCR_013030)

URL: http://www.aniseed.cnrs.fr/

Resource Type: Resource, database, service resource, storage service resource, software resource, data repository, data or information resource

Database of ascidian embryonic development at the level of the genome (cis-regulatory sequences, gene expression, protein annotation), of the cell (morphology, fate, induction, lineage) or of the whole embryo (anatomy, morphogenesis). Currently, four organism models are described in Aniseed: Ciona intestinalis, Ciona savignyi, Halocynthia roretzi and Phallusia mammillata.
This version supports four sets of Ciona intestinalis transcript models: JGI v1.0, KyotoGrail 2005, KH and ENSEMBL, all functionally annotated, and grouped into Aniseedv3.0 gene models. Users can explore their expression profiles during normal or manipulated development, access validated cis-regulatory regions, get the molecular tools used to assay gene function, or all articles related to the function, or regulation of a given gene. Known transcriptional regulators and targets are listed for each gene, as are the gene regulatory networks acting in individual anatomical territories.
ANISEED is a community tool, and the direct involvement of external contributors is important to optimize the quality of the submitted data. Virtual embryo: The 3D Virtual embryo is available to download in the download section of the website.

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    asSeq

Cite this (asSeq, RRID:SCR_001625)

URL: http://bios.unc.edu/~weisun/software/asSeq.htm

Resource Type: Resource, software resource, software application, data analysis software, data processing software, source code

Software that establishes a statistical framework for future developments of eQTL (expression quantitative trait locus) mapping methods using RNA-seq data (e.g., linkage-based eQTL mapping), and the joint study of multiple genetic markers and/or multiple genes. This R package has been submitted to R/bioconductor. It will be available on bioconductor soon. It is recommended to install this R package from bioconductor. You can also install this R package from the source code by yourself. Since the R package contains C code, a C complier is required for installation. With both R and appropriate c complier installed, this R package can be installed using the following command (in Mac Terminal window or Windows command window) R CMD INSTALL asSeq

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Cite this (A statistical framework for genomic data fusion, RRID:SCR_007219)

URL: http://noble.gs.washington.edu/proj/sdp-svm/

Resource Type: Resource, data set, source code, software resource, data or information resource

A statistical framework for genomic data fusion is a computational framework for integrating and drawing inferences from a collection of genome-wide measurements. Each dataset is represented via a kernel function, which defines generalized similarity relationships between pairs of entities, such as genes or proteins. The kernel representation is both flexible and efficient, and can be applied to many different types of data. Furthermore, kernel functions derived from different types of data can be combined in a straightforward fashion. Recent advances in the theory of kernel methods have provided efficient algorithms to perform such combinations in a way that minimizes a statistical loss function. These methods exploit semidefinite programming techniques to reduce the problem of finding optimizing kernel combinations to a convex optimization problem. Computational experiments performed using yeast genome-wide datasets, including amino acid sequences, hydropathy profiles, gene expression data and known protein-protein interactions, demonstrate the utility of this approach. A statistical learning algorithm trained from all of these data to recognize particular classes of proteins--membrane proteins and ribosomal proteins--performs significantly better than the same algorithm trained on any single type of data. Matlab code to center a kernel matrix and Matlab code for normalization are available.

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    Athena

Cite this (Athena, RRID:SCR_008110)

URL: http://www.bioinformatics2.wsu.edu/cgi-bin/Athena/cgi/home.pl

Resource Type: Resource, data or information resource, database

Athena is a web-based application that warehouses disparate datatypes related to the control of gene expression. Athena provides several features to enable exploration of the regulatory mechanisms of Arabidopsis gene control. The first main tool we provide is visualization of promoter domains of selected genes. Database crossreference for these transcription factors is provided as well as a statistical test for enrichment of binding activity within the set of selected promoters. The data mining tools in Athena allow for selection of sets of genes based on two different factors. -Genes can be select by specifying a set of binding factors whose putative sites must be present within all of those genes'' promoter regions. -Alternatively, genes can be selected using Gene Ontology annotations. Both GO (Gene Ontology) Slim terms and Gene Ontology terms are available. One can select a set of genes by either choosing a union of the genes annotated by a selected set of Slim terms or Gene Ontology terms. The selected gene''s putative binding factors are listed, including enrichment data. Furthermore, enriched presence of Gene Ontology terms is given. The analysis suite provides both enhanced data mining tools for selecting genes as well as several data displays.

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