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http://www.stjudebgem.org/web/mainPage/mainPage.php

This database contains gene expression patterns assembled from mouse nervous tissues at 4 time points throughout brain development including embryonic (e) day 11.5, e15.5, postnatal (p) day 7 and adult p42. Using a high throughput in situ hybridization approach we are assembling expression patterns from selected genes and presenting them in a searchable database. The database includes darkfield images obtained using radioactive probes, reference cresyl violet stained sections, the complete nucleotide sequence of the probes used to generate the data and all the information required to allow users to repeat and extend the analyses. The database is directly linked to Pubmed, LocusLink, Unigene and Gene Ontology Consortium housed at the National Center for Biotechnology Information (NCBI) in the National Library of Medicine. These data are provided freely to promote communication and cooperation among research groups throughout the world.

Proper citation: Brain Gene Expression Map (RRID:SCR_001517) Copy   

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http://www.gudmap.org

Project aggregates and provides experimental gene expression data from genito-urinary system. International consortium providing molecular atlas of gene expression for developing organs of GenitoUrinary (GU) tract. Mouse strains to facilitate developmental and functional studies within GU system. Experimental protocols and standard specifications. Tutorials describing GU organogenesis and primary data via database. Data are from large-scale in situ hybridization screens (wholemount and section) and microarray gene expression data of microdissected, laser-captured and FACS-sorted components of developing mouse genitourinary (GU) system.

Proper citation: GenitoUrinary Development Molecular Anatomy Project (RRID:SCR_001554) Copy   

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http://talasso.cnb.csic.es/

Tool for quantification of human miRNA-mRNA Interactions. TaLasso is also available as Matlab or R code.

Proper citation: TaLasso (RRID:SCR_001726) Copy   

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https://www.hgsc.bcm.edu/content/sea-urchin-genome-project

Provides informationa about Genome of California Purple Sea Urchin, one species (Strongylocentrotus purpuratus) of which has been sequenced and annotated by Sea Urchin Genome Sequencing Consortium led by HGSC. Reports sequence and analysis of genome of sea urchin Strongylocentrotus purpuratus, a model for developmental and systems biology.

Proper citation: Sea Urchin Genome Project (RRID:SCR_001735) Copy   

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http://sourceforge.net/projects/dnaclust/

Software program for clustering large number of short similar DNA sequences. It was originally designed for clustering targeted 16S rRNA pyrosequencing reads.

Proper citation: DNACLUST (RRID:SCR_001771) Copy   

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http://www.nitrc.org/projects/plink

Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.

Proper citation: PLINK (RRID:SCR_001757) Copy   

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http://meme-suite.org/

Suite of motif-based sequence analysis tools to discover motifs using MEME, DREME (DNA only) or GLAM2 on groups of related DNA or protein sequences; search sequence databases with motifs using MAST, FIMO, MCAST or GLAM2SCAN; compare a motif to all motifs in a database of motifs; associate motifs with Gene Ontology terms via their putative target genes, and analyze motif enrichment using SpaMo or CentriMo. Source code, binaries and a web server are freely available for noncommercial use.

Proper citation: MEME Suite - Motif-based sequence analysis tools (RRID:SCR_001783) Copy   

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http://www.sanbi.ac.za/resources/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23, 2022. The South African National Bioinformatics Institute delivers biomedical discovery appropriate to both international and African context. Researchers at SANBI perform the highest level of research and provide excellence in education. Research at SANBI has set well recognized milestones in the field of computational biology. The tools and techniques used have not only been developed but also implemented across heterogeneous domains of advanced research. Local and international efforts have driven our discoveries. Until recently, the core of SANBIs research has focused upon gene expression biology. Methods developed and applied at SANBI revolve around a greater understanding of the underlying causes of diseases. SANBI approaches the problem by comparison of genes, genomes and transcriptomes. It uses computational gene expression biology to create novel biological insights and to provide biomarkers for experimental validation. It also performs analysis of human genome variation, transcriptional diversity on both the expression and splicing level and the unravelling of transcriptional regulatory networks. Resources - Hinv, STACKdb, Malaria resources and Trypanosome databases are available for on-line seaching. - SANBI offers WCD, STACKdb, stackPACK and eVOC and the eVOKE viewer as tools that can be downloaded. Sponsors: SANBI receives funding and support from a range of organisations in South Africa and Internationally. Organisations currently supporting SANBI include: South Africa * South African Medical Research Council * South African AIDS Vaccine Initiative * National Bioinformatics Network * National Research Foundation * Claude Leon Foundation * International Business Machines Inc. Europe * European Unions 6th Framework Programme * World Health Organization USA * US National Institutes of Health * Fogarty International Centre * Ludwig Institute for Cancer Research

Proper citation: South African National Bioinformatics Institute: Resources (RRID:SCR_001867) Copy   

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http://pga.gs.washington.edu

The SeattleSNPs PGA is focused on identifying, genotyping, and modeling the associations between single nucleotide polymorphisms (SNPs) in candidate genes and pathways that underlie inflammatory responses in humans. SeattleSNPs is focused on variation analysis in genes related to the inflammatory response. These gene targets are found in specific pathways and from interacting molecules contributing to this response. Available Resources: - Baseline assembled and complete genomic sequence and chromosomal location for candidate gene targets - Mapping of exon and repeat structure for candidate genes - Amplification primers and conditions - SNPs mapped by location in gene structure - SNPs with immediate surrounding sequence for genotype assay design - Genotypes and relative allele frequencies of the SNPs - Special features of SNPs - location (5', coding, etc.), amino acid substitutions, recurrent variation - Manuals on all protocols, data analysis procedures, and use of software tools - Workshop on genetic variation analysis and a gene submission program for variation analysis Sponsors: SeattleSNPs is funded as part of the National Heart Lung and Blood Institute's (NHLBI) Programs for Genomic Applications (PGA).

Proper citation: SeattleSNPs - Variation Discovery Resource (RRID:SCR_001859) Copy   

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http://www.dkfz.de/en/mol_embryology/axeldb.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 21, 2011. Database focusing on gene expression in the frog Xenopus laevis, it is the web companion to the research papers describing a large-scale in situ hybridization screening in Xenopus embryos. The goals of this large-scale in situ screen project are to identify genes by the characterization of their expression pattern, to partially sequence the corresponding cDNAs and to maintain a database collecting the results.

Proper citation: Axel Database (RRID:SCR_001890) Copy   

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http://www-genome.stanford.edu/

This resource hyperlinks to systematic analysis projects, resources, laboratories, and departments at Stanford University.

Proper citation: Stanford Genomic Resourses (RRID:SCR_001874) Copy   

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http://www.oege.org/

Portal for researchers to locate information relevant to interpretation and follow-up of human genetic epidemiological discoveries, including: a range of population and case and family genetic epidemiological studies, relevant gene and sequence databases, genetic variation databases, trait measurement, resource labs, journals, software, general information, disease genes and genetic diversity.

Proper citation: Online Encyclopedia for Genetic Epidemiology studies (RRID:SCR_001825) Copy   

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http://scicrunch.org

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2019.

Database for those interested in the consequences of Factor VIII genetic variation at the DNA and protein level, it provides access to data on the molecular pathology of haemophilia A. The database presents a review of the structure and function of factor VIII and the molecular genetics of haemophilia A, a real time update of the biostatistics of each parameter in the database, a molecular model of the A1, A2 and A3 domains of the factor VIII protein (based on the crystal structure of caeruloplasmin) and a bulletin board for discussion of issues in the molecular biology of factor VIII. The database is completely updated with easy submission of point mutations, deletions and insertions via e-mail of custom-designed forms. A methods section devoted to mutation detection is available, highlighting issues such as choice of technique and PCR primer sequences. The FVIII structure section now includes a download of a FVIII A domain homology model in Protein Data Bank format and a multiple alignment of the FVIII amino-acid sequences from four species (human, murine, porcine and canine) in addition to the virtual reality simulations, secondary structural data and FVIII animation already available. Finally, to aid navigation across this site, a clickable roadmap of the main features provides easy access to the page desired. Their intention is that continued development and updating of the site shall provide workers in the fields of molecular and structural biology with a one-stop resource site to facilitate FVIII research and education. To submit your mutants to the Haemophilia A Mutation Database email the details. (Refer to Submission Guidelines)

Proper citation: HAMSTeRS - The Haemophilia A Mutation Structure Test and Resource Site (RRID:SCR_006883) Copy   

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http://sourceforge.net/p/fastsemsim/home/Home/

A package that implements several semantic similarity measures. It is both a library and an end-user application, featuring an intuitive graphical user interface (GUI). It has been implemented with the aim of being fast, expandable, and easy to use. It allows the user to work with the most updated version of GO database and customizable annotation corpora. It provides a set of logically-organized classes that can be easily exploited to both integrate semantic similarity into different analysis pipelines and extend the library with new measures. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FastSemSim (RRID:SCR_006919) Copy   

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http://gtrnadb.ucsc.edu

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.

Proper citation: GtRNAdb - Genomic tRNA Database (RRID:SCR_006939) Copy   

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http://www.europhenome.org

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.

Proper citation: Europhenome Mouse Phenotyping Resource (RRID:SCR_006935) Copy   

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http://autismkb.cbi.pku.edu.cn/

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.

Proper citation: AutismKB (RRID:SCR_006937) Copy   

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http://www.dkfz.de/en/mga/Groups/LIFEdb-Database.html

Database that integrates large-scale functional genomics assays and manual cDNA annotation with bioinformatics gene expression and protein analysis. LifeDB integrates data regarding full length cDNA clones and data on expression of encoded protein and their subcellular localization on mammalian cell line. LifeDB enables the scientific community to systematically search and select genes, proteins as well as cDNA of interest by specific database identifiers as well as gene name. It enables to visualize cDNA clone and subcellular location of proteins. It also links the results to external biological databases in order to provide a broader functional information. LifeDB also provides an annotation pipeline which facilitates an improved mapping of clones to known human reference transcripts from the RefSeq database and the Ensembl database. An advanced web interface enables the researchers to view the data in a more user friendly manner. Users can search using any one of the following search options available both in Search gene and cDNA clones and Search Sub-cellular locations of human proteins: By Keyword, By gene/transcript identifier, By plate name, By clone name, By cellular location. * The Search genes and cDNA clones results include: Gene Name, Ensemble ID, Genomic Region, Clone name, Plate name, Plate position, Classification class, Synonymous SNP''s, Non- synonymous SNP''s, Number of ambiguous positions, and Alignment with reference genes. * The Search sub-cellular locations of human proteins results include: Subcellular location, Gene Name, Ensemble ID, Clone name, True localization, Images, Start tag and End tag. Every result page has an option to download result data (excluding the microscopy images). On click of ''Download results as CSV-file'' link in the result page the user will be given a choice to open or save result data in form of a CSV (Comma Separated Values) file. Later the CSV file can be easily opened using Excel or OpenOffice.

Proper citation: LifeDB (RRID:SCR_006899) Copy   

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https://mctfr.psych.umn.edu/

Composed of many projects, including the Minnesota Twin Family Study (MTFS) and The Sibling Interaction and Behavior Study (SIBS), this research center seeks to identify genetic and environmental influences on development and psychological traits. Both projects are longitudinal research studies including twins, siblings, and parents. Over 9800 individuals have contributed to these exciting projects! By studying twins and siblings and their families, we can estimate how genes and environment interact to influence character, strengths, vulnerabilities and values. Participants in the MTFS include families with same-sex identical or fraternal twins who were born in Minnesota. The SIBS study is comprised of adoptive and biological siblings and their parents. Most participants partake in day-long visits to the MCTFR, and due to the longitudinal nature of our projects, they return every 3-4 years for follow-up visits.

Proper citation: Minnesota Center for Twin and Family Research (RRID:SCR_006948) Copy   

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http://www.nervenet.org/main/dictionary.html

A mouse-related portal of genomic databases and tables of mouse brain data. Most files are intended for you to download and use on your own personal computer. Most files are available in generic text format or as FileMaker Pro databases. The server provides data extracted and compiled from: The 2000-2001 Mouse Chromosome Committee Reports, Release 15 of the MIT microsatellite map (Oct 1997), The recombinant inbred strain database of R.W. Elliott (1997) and R. W. Williams (2001), and the Map Manager and text format chromosome maps (Apr 2001). * LXS genotype (Excel file): Updated, revised positions for 330 markers genotyped using a panel of 77 LXS strain. * MIT SNP DATABASE ONLINE: Search and sort the MIT Single Nucleotide Polymorphism (SNP) database ONLINE. These data from the MIT-Whitehead SNP release of December 1999. * INTEGRATED MIT-ROCHE SNP DATABASE in EXCEL and TEXT FORMATS (1-3 MB): Original MIT SNPs merged with the new Roche SNPs. The Excel file has been formatted to illustrate SNP haplotypes and genetic contrasts. Both files are intended for statistical analyses of SNPs and can be used to test a method outlined in a paper by Andrew Grupe, Gary Peltz, and colleagues (Science 291: 1915-1918, 2001). The Excel file includes many useful equations and formatting that will help in navigating through this large database and in testing the in silico mapping method. * Use of inbred strains for the study of individual differences in pain related phenotypes in the mouse: Elissa J. Chesler''s 2002 dissertation, discussing issues relevant to the integration of genomic and phenomic data from standard inbred strains including genetic interactions with laboratory environmental conditions and the use of various in silico inbred strain haplotype based mapping algorithms for QTL analysis. * SNP QTL MAPPER in EXCEL format (572 KB, updated January 2002 by Elissa Chesler): This Excel workbook implements the Grupe et al. mapping method and outputs correlation plots. The main spreadsheet allows you to enter your own strain data and compares them to haplotypes. Be very cautious and skeptical when using this spreadsheet and the technique. Read all of the caveates. This excel version of the method was developed by Elissa Chesler. This updated version (Jan 2002) handles missing data. * MIT SNP Database (tab-delimited text format): This file is suitable for manipulation in statistics and spreadsheet programs (752 KB, Updated June 27, 2001). Data have been formatted in a way that allows rapid acquisition of the new data from the Roche Bioscience SNP database. * MIT SNP Database (FileMaker 5 Version): This is a reformatted version of the MIT Single Nucleotide Polymorphism (SNP) database in FileMaker 5 format. You will need a copy of this application to open the file (Mac and Windows; 992 KB. Updated July 13, 2001 by RW). * Gene Mapping and Map Manager Data Sets: Genetic maps of mouse chromosomes. Now includes a 10th generation advanced intercross consisting of 500 animals genetoyped at 340 markers. Lots of older files on recombinant inbred strains. * The Portable Dictionary of the Mouse Genome, 21,039 loci, 17,912,832 bytes. Includes all 1997-98 Chromosome Committee Reports and MIT Release 15. * FullDict.FMP.sit: The Portable Dictionary of the Mouse Genome. This large FileMaker Pro 3.0/4.0 database has been compressed with StuffIt. The Dictionary of the Mouse Genome contains data from the 1997-98 chromosome committee reports and MIT Whitehead SSLP databases (Release 15). The Dictionary contains information for 21,039 loci. File size = 4846 KB. Updated March 19, 1998. * MIT Microsatellite Database ONLINE: A database of MIT microsatellite loci in the mouse. Use this FileMaker Pro database with OurPrimersDB. MITDB is a subset of the Portable Dictionary of the Mouse Genome. ONLINE. Updated July 12, 2001. * MIT Microsatellite Database: A database of MIT microsatellite loci in the mouse. Use this FileMaker Pro database with OurPrimersDB. MITDB is a subset of the Portable Dictionary of the Mouse Genome. File size = 3.0 MB. Updated March 19, 1998. * OurPrimersDB: A small database of primers. Download this database if you are using numerous MIT primers to map genes in mice. This database should be used in combination with the MITDB as one part of a relational database. File size = 149 KB. Updated March 19, 1998. * Empty copy (clone) of the Portable Dictionary in FileMaker Pro 3.0 format. Download this file and import individual chromosome text files from the table into the database. File size = 231 KB. Updated March 19, 1998. * Chromosome Text Files from the Dictionary: The table lists data on gene loci for individual chromosomes.

Proper citation: Mouse Genome Databases (RRID:SCR_007147) Copy   

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