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http://gerg01.gsc.riken.jp/cage/mm5

A web system, which could search and display to current CAGE library information in CAGE Database.

Proper citation: CAGE Basic Viewer for Mus musculus (RRID:SCR_000451) Copy   

•   Source: SciCrunch Registry

http://anya.igsb.anl.gov/Geneways/GeneWays.html

System for automatically extracting, analzying, visualizing and integrating molecular pathway data from the research literature. System focuses on interactions between molecular substances and actions, providing a graphical consensus view on the collected information. GeneWays is designed as open platform, allowing researchers to query, review and critique integrated information.

Proper citation: GeneWays (RRID:SCR_000572) Copy   

•   Source: SciCrunch Registry

http://bowtie-bio.sourceforge.net/recount/

RNA-seq gene count datasets built using the raw data from 18 different studies. The raw sequencing data (.fastq files) were processed with Myrna to obtain tables of counts for each gene. For ease of statistical analysis, they combined each count table with sample phenotype data to form an R object of class ExpressionSet. The count tables, ExpressionSets, and phenotype tables are ready to use and freely available. By taking care of several preprocessing steps and combining many datasets into one easily-accessible website, we make finding and analyzing RNA-seq data considerably more straightforward.

Proper citation: ReCount - A multi-experiment resource of analysis-ready RNA-seq gene count datasets (RRID:SCR_001774) Copy   

•   Source: SciCrunch Registry

http://cistrome.org/finder

Data portal that can help query, evaluate and visualize publicly available Chromatin immunoprecipitation and DNase I hypersensitivity assays with high-throughput sequencing data in human and mouse. The database currently contains 6378 samples over 4391 datasets, 313 factors and 102 cell lines or cell populations (May 2013). Each dataset has gone through a consistent analysis and quality control pipeline; therefore, users could evaluate the overall quality of each dataset before examining binding sites near their genes of interest. CistromeFinder is integrated with UCSC genome browser for visualization, Primer3Plus for ChIP-qPCR primer design and CistromeMap for submitting newly available datasets. It also allows users to leave comments to facilitate data evaluation and update.

Proper citation: CistromeFinder (RRID:SCR_005405) Copy   

•   Source: SciCrunch Registry

http://www.ucl.ac.uk/cardiovasculargeneontology/

Full Gene Ontology annotation to genes associated with cardiovascular processes. Every GO annotation made, is attributed to an identified source, such as a publication identifier (PMID), and an indication of the type of evidence which supports the association between the gene product and the GO term. Over 4,000 cardiovascular associated genes have been identified. A variety of tools have been provided to enable cardiovascular scientists to review the annotation of their ''''favorite'''' gene and suggest information that may be missing, inaccurate or incomplete in these annotations. Annotation suggestions can be sent through the feedback form or by email. The Gene Ontology (GO) vocabulary is the established standard for the functional annotation of gene products. By using GO to curate scientific literature and by integrating results from high-quality high-throughput experiments they will create an information-rich resource for the cardiovascular-research community, enabling researchers to rapidly evaluate and interpret existing data and generate hypotheses to guide future research.

Proper citation: Cardiovascular Gene Ontology Annotation Initiative (RRID:SCR_004795) Copy   

•   Source: SciCrunch Registry

http://www.broad.mit.edu/mpr/lung

Data set of a molecular taxonomy of lung carcinoma, the leading cause of cancer death in the United States and worldwide. Using oligonucleotide microarrays, researchers analyzed mRNA expression levels corresponding to 12,600 transcript sequences in 186 lung tumor samples, including 139 adenocarcinomas resected from the lung. Hierarchical and probabilistic clustering of expression data defined distinct sub-classes of lung adenocarcinoma. Among these were tumors with high relative expression of neuroendocrine genes and of type II pneumocyte genes, respectively. Retrospective analysis revealed a less favorable outcome for the adenocarcinomas with neuroendocrine gene expression. The diagnostic potential of expression profiling is emphasized by its ability to discriminate primary lung adenocarcinomas from metastases of extra-pulmonary origin. These results suggest that integration of expression profile data with clinical parameters could aid in diagnosis of lung cancer patients.

Proper citation: Classification of Human Lung Carcinomas by mRNA Expression Profiling Reveals Distinct Adenocarcinoma Sub-classes (RRID:SCR_003010) Copy   

•   Source: SciCrunch Registry

http://eyebrowse.cit.nih.gov/

EyeBrowse displays expressed sequence tag (EST) cDNA clones from eye tissues (derived from NEIBank and other sources) aligned with current versions of the human, rhesus, mouse, rat, dog, cow, chicken, or zebrafish genomes, including reference sequences for known genes. This gives a simplified view of gene expression activity from different parts of the eye across the genome. The data can be interrogated in several ways. Specific gene names can be entered into the search window. Alternatively, regions of the genome can be displayed. For example, entering two STS markers separated by a semicolon (e.g. RH18061;RH80175) allows the display of the entire chromosomal region associated with the mapping of a specific disease locus. ESTs for each tissue can then be displayed to help in the selection of candidate genes. In addition, sequences can be entered into a BLAT search and rapidly aligned on the genome, again showing eye derived ESTs for the same region. EyeBrowse includes a custom track display SAGE data for human eye tissues derived from the EyeSAGE project. The track shows the normalized sum of SAGE tag counts from all published eye-related SAGE datasets centered on the position of each identifiable Unigene cluster. This indicates relative activity of each gene locus in eye. Clicking on the vertical count bar for a particular location will bring up a display listing gene details and linking to specific SAGE counts for each eye SAGE library and comparisons with normalized sums for neural and non-neural tissues. To view or alter settings for the EyeSAGE track on EyeBrowse, click on the vertical gray bar at the left of the display. Other custom tracks display known eye disease genes and mapped intervals for candidate loci for retinal disease, cataract, myopia and cornea disease. These link back to further information at NEIBank. For mouse, there is custom track data for ChIP-on-Chip of RNA-Polymerase-II during photoreceptor maturation.

Proper citation: EyeBrowse (RRID:SCR_008000) Copy   

•   Source: SciCrunch Registry

http://www.stanford.edu/~rnusse/pathways/targets.html

A list of target genes of Wnt/beta-catenin signaling. Suggestions for additions are welcome. Direct targets are defined as those with Tcf binding sites and demonstrating that these sites are important.

Proper citation: Target genes of Wnt/beta-catenin signaling (RRID:SCR_007022) Copy   

•   Source: SciCrunch Registry

http://www.icmic.net/

Imaging core offering multiple small animal imaging modalities including MicroSPECT, Optical imaging, MicroCT and Ultrasound have been centralized together with a unit for probe development and a vivarium for the housing of animals in one laboratory.

Proper citation: In-Vivo Cellular and Molecular Imaging Center, Brussels (RRID:SCR_008047) Copy   

•   Source: SciCrunch Registry

http://casestudies.brain-map.org/celltax

Cellular Taxonomy of Mouse Visual Cortex by analyzing gene expression patterns at single cell level. Construction of cellular taxonomy of one cortical region, primary visual cortex, in adult mice done on basis of single cell RNA sequencing.

Proper citation: CellTax vignette (RRID:SCR_017000) Copy   

•   Source: SciCrunch Registry

https://www.umassmed.edu/tkomouse/

Core to produce genetically modified mice, rats, and stem cells for the UMMS Scientific Community.Composed of two facilities: Animal Modeling Facility and Gene Targeting and Stem Cell Facility.

Proper citation: Massachusetts University Medical School Transgenic Animal Modeling Core Facility (RRID:SCR_017729) Copy   

•   Source: SciCrunch Registry

https://sdrc.stanford.edu/sdrc-research-cores/dgac/home/

Core facility that offers library preparation and sequencing services on a variety of platforms - Illumina HiSeq 4000, MiSeq, HiSeq 2500 and PacBio Sequel - as well as bioinformatics analysis. It can sequence a variety of commercial sample preparation kits as well as custom workflows. DGAC provides access to high throughput sequencing and analysis to researchers at the Stanford Diabetes Research Center.

Proper citation: Stanford Diabetes Research Center Diabetes Genomics Analysis Core (RRID:SCR_016213) Copy   

•   Source: SciCrunch Registry

http://www.unmc.edu/ecf/

Core assists with epigenetic analysis including DNA Methylation, Chromatin Immunoprecipitation and Real Time Quantitative PCR gene expression analysis. Services include DNA Methylation Analysis, Specific Genomic Location Analysis:Methylation Specific PCR,Bisulfite Sequencing,Bisulfite Pyrosequencing,Qiagen PyroMark Pyrosequencer Instrumentation;Genome Wide Analysis:High Throughput Sequencing Methylation Analysis, Methyl-Sensitive Cut Counting (MSCC),Methyl CpG Binding Domain - Isolated Genome Sequencing (MiGS);Chromatin Immunoprecipitation Analysis (ChIP):Analysis of Histone Modifications,DNA-Protein Interactions,Chromatin Positions analyzed using:Quantitative PCR Analysis (Real-Time QPCR),High Throughput Sequencing Analysis (ChIP-Seq);Gene Expression Analysis (QPCR):Real-Time Quantitative PCR Gene Expression.

Proper citation: Nebraska University Medical Center Epigenomics Core Facility (RRID:SCR_017800) Copy   

•   Source: SciCrunch Registry

https://www.biotech.wisc.edu/services/gec

Core provides RNA library preparation services for Illumina, PacBio and Oxford Nanopore sequencing platforms. Single Cell RNA and Spatial Transcriptomics services are available with 10X Genomics technology. Provides RNA extraction, RNA QC and SNP genotyping and methylation bead array services. Provides support from project design through downstream analysis.Service facility, from hypothesis to publication.Microarray: expression and genotyping Affymetrix, Agilent, Nimblegen. Sequencing: RNA, gDNA, ChIP, Capture, 16SNovaSeq, HiSeq 2500, 3000, MiSeq.

Proper citation: Wisconsin-Madison University Biotechnology Center Gene Expression Center Core Facility (RRID:SCR_017757) Copy   

•   Source: SciCrunch Registry

http://www.bumc.bu.edu/microarray/

Core provides analysis of gene expression using Affymetrix GeneChip platform. Offers next generation sequencing via Illumina NextSeq and Ion Torrent PGM and Proton instruments, analysis of RNA and DNA using Agilent Bioanalyzer.

Proper citation: Boston University Microarray and Sequencing Resource Core Facility (RRID:SCR_017782) Copy   

•   Source: SciCrunch Registry

http://hihg.med.miami.edu/cgt/gene-expression

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 27,2025. CGT gene expression core utilizes Affymetrix GeneChip Arrays and Illumina BeadChips to identify gene expression variation in single genes, targeted set of genes, or entire genomes. Affymetrix GeneChip Arrays Human Gene ST,Human Transcriptome Array 2.0, Human Exon ST, Human miRNA, Illumina Expression, HumanHT-12 v4 BeadChip.

Proper citation: University of Miami Miller School of Medicine Gene Expression Core Facility (RRID:SCR_017825) Copy   

•   Source: SciCrunch Registry

http://cancercontrol.cancer.gov/tcrb/tturc/

A transdisciplinary approach to the full spectrum of basic and applied research on tobacco use to reduce the disease burden of tobacco use, including: * Etiology of tobacco use and addiction * Impact of advertising and marketing * Prevention of tobacco use * Treatment of tobacco use and addiction * Identification of biomarkers of tobacco exposure * Identification of genes related to addiction and susceptibility to harm from tobacco Goals * Increase the number of investigators from relevant disciplines who focus on the study of tobacco use as part of transdisciplinary teams. * Generate basic research evidence to improve understanding of the etiology and natural history of tobacco use. * Produce evidence-based tobacco use interventions that can translate to the community and specific understudied or underserved populations. * Increase the number of evidence-based interventions that are novel, including the development, testing and dissemination of innovative behavioral treatments and prevention strategies based upon findings from basic research. * Train transdisciplinary investigators capable of conducting cutting-edge tobacco use research. * Increase the number of peer-reviewed publications in the areas of tobacco use, nicotine addiction, and treatment.

Proper citation: Transdisciplinary Tobacco Use Research Centers (RRID:SCR_006858) Copy   

•   Source: SciCrunch Registry

http://androgendb.mcgill.ca/

Comprehensive listing of androgen receptor gene mutations published in journals and meetings proceedings. The majority of mutations are point mutations identified in patients with androgen insensitivity syndrome. Information is included regarding the phenotype, the nature and location of the mutations, as well as the effects of the mutations on the androgen binding activity of the receptor. In light of the difficulty in getting new AR mutations published the curator will now accept new mutations that have not been published, provided that it is from a reputable research or clinical laboratory. The database incorporates information on the exon 1 CAG repeat expansion disease, spinobulbar muscular atrophy (SBMA), as well as CAG repeat length variations associated with risk for female breast, uterine endometrial, colorectal, and prostate cancer, as well as for male infertility. The possible implications of somatic mutations, as opposed to germline mutations, in the development of future locus-specific mutation databases (LSDBs) is discussed.
The database now provides information on the external genitalia and on sex - of - rearing. Additionally, the new version of the database has an entry to show if pathogenicity has been proven. A pdf and fully searchable version of the Database is available for download.

Proper citation: Androgen Receptor Gene Mutations Database (RRID:SCR_006887) Copy   

•   Source: SciCrunch Registry

http://159.149.160.51/cscan/

Data resource that includes a large collection of genome-wide ChIP-Seq experiments performed on transcription factors (TFs), histone modifications, RNA polymerases and others. Enriched peak regions from the ChIP-Seq experiments are crossed with the genomic coordinates of a set of input genes, to identify which of the experiments present a statistically significant number of peaks within the input genes' loci. The input can be a cluster of co-expressed genes, or any other set of genes sharing a common regulatory profile. Users can thus single out which TFs are likely to be common regulators of the genes, and their respective correlations. Also, by examining results on promoter activation, transcription, histone modifications, polymerase binding and so on, users can investigate the effect of the TFs (activation or repression of transcription) as well as of the cell or tissue specificity of the genes' regulation and expression.

Proper citation: Cscan (RRID:SCR_006756) Copy   

•   Source: SciCrunch Registry

http://brainmaps.org

An interactive multiresolution brain atlas that is based on over 20 million megapixels of sub-micron resolution, annotated, scanned images of serial sections of both primate and non-primate brains and integrated with a high-speed database for querying and retrieving data about brain structure and function. Currently featured are complete brain atlas datasets for various species, including Macaca mulatta, Chlorocebus aethiops, Felis catus, Mus musculus, Rattus norvegicus, Tyto alba and many other vertebrates. BrainMaps is currently accepting histochemical, immunocytochemical, and tracer connectivity data, preferably whole-brain. In addition, they are interested in EM, MRI, and DTI data.

Proper citation: BrainMaps.org (RRID:SCR_006878) Copy   

•   Source: SciCrunch Registry