Tools   Select Another Resource Report Type

http://www.genome.jp/kegg/expression/

Database for mapping gene expression profiles to pathways and genomes. Repository of microarray gene expression profile data for Synechocystis PCC6803 (syn), Bacillus subtilis (bsu), Escherichia coli W3110 (ecj), Anabaena PCC7120 (ana), and other species contributed by the Japanese research community.

Proper citation: Kyoto Encyclopedia of Genes and Genomes Expression Database (RRID:SCR_001120) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/CGEN.html

Software R package for analysis of case-control studies in genetic epidemiology.

Proper citation: CGEN (RRID:SCR_001251) Copy   

•   Source: SciCrunch Registry

http://med.stanford.edu/tanglab/software/saber.html

Software program suitable for genome-scale data which uses a Markov-hidden Markov model (MHMM) to estimate local ancestry. The MHMM makes it possible to identify genomic blocks of a particular ancestry by use of any high-density single-nucleotide-polymorphism panel. One application is to perform admixture mapping without genotyping special ancestry-informative-marker panels.

Proper citation: SABER (RRID:SCR_001257) Copy   

•   Source: SciCrunch Registry

http://www.wpic.pitt.edu/wpiccompgen/GemTools/GemTools.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software tools for modeling genetic ancestry based on the single nucleotide polymorphism (SNP) information. This package of functions helps the user account for genetic ancestry of a large number of individuals using spectral graph theory and projections to break a large problem into smaller pieces and calculate genetic ancestry information efficiently, i.e., a divide and conquer (dac) strategy. It is completely written in R and runs on any platform that supports R.

Proper citation: GemTools (RRID:SCR_001259) Copy   

•   Source: SciCrunch Registry

http://www.morpholinodatabase.org/

Central database to house data on morpholino screens currently containing over 700 morpholinos including control and multiple morpholinos against the same target. A publicly accessible sequence-based search opens this database for morpholinos against a particular target for the zebrafish community. Morpholino Screens: They set out to identify all cotranslationally translocated genes in the zebrafish genome (Secretome/CTT-ome). Morpholinos were designed against putative secreted/CTT targets and injected into 1-4 cell stage zebrafish embryos. The embryos were observed over a 5 day period for defects in several different systems. The first screen examined 184 gene targets of which 26 demonstrated defects of interest (Pickart et al. 2006). A collaboration with the Verfaillie laboratory examined the knockdown of targets identified in a comparative microarray analysis of hematopoietic stem cells demonstrating how microarray and morpholino technologies can be used in conjunction to enrich for defects in specific developmental processes. Currently, many collaborations are underway to identify genes involved in morphological, kidney, skin, eye, pigment, vascular and hematopoietic development, lipid metabolism and more. The screen types referred to in the search functions are the specific areas of development that were examined during the various screens, which include behavior, general morphology, pigmentation, toxicity, Pax2 expression, and development of the craniofacial structures, eyes, kidneys, pituitary, and skin. Only data pertaining to specific tests performed are presented. Due to the complexity of this international collaboration and time constraints, not all morpholinos were subjected to all screen types. They are currently expanding public access to the database. In the future we will provide: * Mortality curves and dose range for each morpholino * Preliminary data regarding the effectiveness of each morpholino * Expanded annotation for each morpholino * External linkage of our morpholino sequences to ZFIN and Ensembl. To submit morpholino-knockdown results to MODB please contact the administrator for a user name and password.

Proper citation: Morpholino Database (RRID:SCR_001378) Copy   

•   Source: SciCrunch Registry

http://www.well.ox.ac.uk/happy/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software package for Multipoint QTL Mapping in Genetically Heterogeneous Animals (entry from Genetic Analysis Software) The method is implemented in a C-program and there is now an R version of HAPPY. You can run HAPPY remotely from their web server using your own data (or try it out on the data provided for download).

Proper citation: Happy (RRID:SCR_001395) Copy   

•   Source: SciCrunch Registry

http://knightadrc.wustl.edu/

The Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) supports researchers and our surrounding community in their pursuit of answers that will lead to improved diagnosis and care for persons with Alzheimer disease (AD). The Center is committed to the long-term goal of finding a way to effectively treat and prevent AD. The Knight ADRC facilitates advanced research on the clinical, genetic, neuropathological, neuroanatomical, biomedical, psychosocial, and neuropsychological aspects of Alzheimer disease, as well as other related brain disorders.

Proper citation: Washington University School of Medicine Knight Alzheimers Disease Research Center (RRID:SCR_000210) Copy   

•   Source: SciCrunch Registry

http://statgenpro.psychiatry.hku.hk/limx/kggseq/

A biological Knowledge-based mining platform for Genomic and Genetic studies using Sequence data. The software platform, constituted of bioinformatics and statistical genetics functions, makes use of valuable biologic resources and knowledge for sequencing-based genetic mapping of variants / genes responsible for human diseases / traits. It facilitates geneticists to fish for the genetic determinants of human diseases / traits in the big sea of DNA sequences. KGGSeq has paid attention to downstream analysis of genetic mapping. The framework was implemented to filter and prioritize genetic variants from whole exome sequencing data.

Proper citation: KGGSeq (RRID:SCR_005311) Copy   

•   Source: SciCrunch Registry

http://www.nbiadisorders.org/

The NBIA Disorders Association, formerly known as Hallervorden-Spatz Syndrome Association, (HSSA) was originally founded in 1996 by President, Patricia Wood. The goals of the association are to raise funds to support research pertinent to NBIA; to provide emotional support to those afflicted with NBIA and their families; and to raise public awareness of NBIA. The NBIA Disorders Association is accepting applications for one-year grants for clinical and translational research studies related to the early detection, diagnosis, or treatment of patients with NBIA. Neurodegeneration with Brain Iron Accumulation (NBIA) is a group of rare, genetic, neurological disorders characterized by the accumulation of iron deposits in the brain and progressive degeneration of the nervous system. It typically first appears in childhood. Presenting signs and symptoms may include difficulty walking, loss of balance, and problems related to speech. Those affected suffer a progressive loss of muscle control, sudden involuntary muscle spasms, and uncontrolled tightening of the muscles. Symptoms may also include disorientation, seizures, and deterioration of intellectual ability. Approximately half of the cases diagnosed have been linked to a mutation of a gene known as PANK2. At the present time, symptoms may be treated but there is no cure. The purpose of the NBIA Disorders Association Research Grant Program is to encourage meritorious research studies designed to improve the diagnosis or treatment of NBIA. The research can be conducted in the United States, countries of the European Union, Canada, Australia, New Zealand, Brazil, Argentina, Chile, South Africa, Japan, or Israel, and in other countries where adequate supervision of grant administration is possible. Grants will be awarded to qualified researchers to initiate pilot studies, the results of which are intended to be used to obtain larger multi-year grant funding. Evaluation of proposals will follow NIH guidelines and include careful consideration of experimental or protocol design, objectivity or relevance of parameters measured, and statistical analysis plan. Proposals that address the following areas will be given priority: * Therapeutics Development: ** Development of pantethine and its derivatives ** Development of other rational therapeutics * Animal & Cellular Models: ** Development of a new rodent disease model by targeted insertion of a ''human disease'' mutation into Pank2 ** Development of induced pluripotent stem cell lines. *** Development of animal and cellular models will be considered for multi-year funding with adequate budget justification. Proposals should detail a research plan and a budget for the initial phase of the work, with the option to contract further work out to a commercial enterprise. * Biomarker Discovery and Assay Development: ** Metabolomics ** Coenzyme A / acyl coenzyme A measurement using accessible (peripheral and central) tissue/fluid * New NBIA gene discovery

Proper citation: NBIA Disorders Association (RRID:SCR_005382) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/gtr/

Central location for voluntary submission of genetic test information by providers including the test''s purpose, methodology, validity, evidence of the test''s usefulness, and laboratory contacts and credentials. GTR aims to advance the public health and research into the genetic basis of health and disease. GTR is accepting registration of clinical tests for Mendelian disorders, complex tests and arrays, and pharmacogenetic tests. These tests may include multiple methods and may include multiple major method categories such as biochemical, cytogenetic, and molecular tests. GTR is not currently accepting registration of tests for somatic disorders, research tests or direct-to-consumer tests.

Proper citation: Genetic Testing Registry (RRID:SCR_005565) Copy   

•   Source: SciCrunch Registry

http://www.biomedbridges.eu/

Consortium of 12 Biomedical sciences research infrastructure (BMS RI) partners to develop a shared e-infrastructure to allow interoperability between data and services in the biological, medical, translational and clinical domains (providing a complex knowledge environment comprising standards, ontologies, data and services) and thus strengthen biomedical resources in Europe. The BMS RIs are on the roadmap of the European Strategy Forum on Research Infrastructures (ESFRI). Connecting several European research infrastructures brings a diversity of ethical, legal and security concerns including data security requirements for participating e-Infrastructures that are storing or processing patient-related data (or biosamples): EATRIS, ECRIN, BBMRI, EuroBioImaging and EMBL-EBI. In addition, INSTRUCT is interested in secure sample transport and in intellectual property rights; Infrafrontier stores high-throughput data from mice. BBMRI with its focus on the availability of biomaterials is currently emphasizing aspects like k-anonymity and metadata management for its data. Sharing of imaging data by Euro-BioImaging poses challenges with respect to anonymisation and intellectual property. Therefore, an ethical, regulatory and security framework for international data sharing that covers these diverse areas and different types of data (e.g. clinical trials data, mouse data, and human genotype and DNA sequence data) is of crucial importance. The outcomes will lead to real and sustained improvement in the services the biomedical sciences research infrastructures offer to the research community. Data curation and sample description will be improved by the adoption of best practices and agreed standards. Many improvements will emerge from new interactions between RIs created by data linkage and networking. Ensuring access to relevant information for all life science researchers across all BMS RIs will enable scientists to conduct and share cutting-edge research.

Proper citation: BioMedBridges (RRID:SCR_006179) Copy   

•   Source: SciCrunch Registry

https://www.snpstats.net/

A web-based application designed from a genetic epidemiology point of view to analyze association studies using single nucleotide polymorphisms (SNPs). For each selected SNP, you will receive: * Allele and genotype frequencies * Test for Hardy-Weinberg equilibrium * Analysis of association with a response variable based on linear or logistic regression * Multiple inheritance models: co-dominant, dominant, recessive, over-dominant and additive * Analysis of interactions (gene-gene or gene-environment) If multiple SNPs are selected: * Linkage disequilibrium statistics * Haplotype frequency estimation * Analysis of association of haplotypes with the response * Analysis of interactions (haplotypes-covariate)

Proper citation: SNPSTATS (RRID:SCR_002142) Copy   

•   Source: SciCrunch Registry

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

Portal for studies of genome structure and genetic variation, gene expression and gene function. Provides 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 commercially available microarray tools from Affymetrix, Illumina, Agilent and Nimblegen, Parentage testing using microsatellites and smaller SNP panels. ARK-Genomics has developed 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 analysis of data often in conjunction with commercial partners.

Proper citation: ARK-Genomics: Centre for Functional Genomics (RRID:SCR_002214) Copy   

•   Source: SciCrunch Registry

http://ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23, 2019.BGMUT was database that provided publicly accessible platform for DNA sequences and curated set of blood mutation information. Data Archive are available at ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive.

Proper citation: Blood Group Antigen Gene Mutation Database (RRID:SCR_002297) Copy   

•   Source: SciCrunch Registry

https://www.drugabuse.gov/publications/drugfacts/genetics-epigenetics-addiction

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. An archived video on the web providing comprehensive and hands-on training in genetics and epigenetic methodology. The purpose of the course is to provide an introduction to approaches and tools for identifying genes that confer vulnerability to addiction and individual differences in responses to treatments. The course is targeted to those who are new to the field of addiction genetics. The course was held over 5 days with lectures and hands-on demonstrations given each day. Viewers of the course will gain familiarity with conceptual and practical approaches to complex disorders using relevant genetic and epigenetic databases, and appropriate statistical and empirical approaches. Topics covered Behavioral genetics, genetic epidemiology, twin and adoption studies, statistical genetic concepts and approaches for mapping complex traits, haplotype based approaches for association mapping, genome-wide scans for addictive disorders, application of linkage for mapping genes and genetic loci for addictive disorders, pharmacogenomics of treatment of addictive disorders, Baysian Methods for identifying gene-gene interactions, analysis of copy number variation, practical use of genetic databases, mapping of complex traits in mice, methods for analyzing gene expression, and methods for doing epigenetic analysis are covered. The course was held April 4, 2008, at the Bethesda North Marriott Hotel and Conference Center, 5701 Marinelli Road, Bethesda, MD 20852.

Proper citation: Short Course on the Genetics and Epigenetics of Addiction National Institute on Drug Abuse: Archived Video (RRID:SCR_002783) Copy   

•   Source: SciCrunch Registry

http://wwwmgs.bionet.nsc.ru/mgs/gnw/about.shtml

GeneNetWorks is designed for accumulation of experimental data, data navigation, data analysis, and analysis of dependencies in the field of gene expression regulation. It integrates the databases and programs for processing the data about structure and function of DNA, RNA, and proteins, together with the other information resources important for gene expression description. The unique property of above described system is that all the resources within the system GeneNetWorks are divided according to the natural hierarchy of molecular genetic systems and has the following levels: (1) DNA; (2) RNA; (3) proteins; and (4) gene networks. Each module contains: 1) experimental data represented as a database or some sample; 2) program for data analysis; 3) results of an automated data processing; 4) tools for the graphical representation of these data and the results of the data analyses.

Proper citation: GeneNetWorks (RRID:SCR_008034) Copy   

•   Source: SciCrunch Registry

http://ncv.unl.edu/Angelettilab/HPV/Database.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented August 23, 2016. The Human Papillomaviruses Database collects, curates, analyzes, and publishes genetic sequences of papillomaviruses and related cellular proteins. It includes molecular biologists, sequence analysts, computer technicians, post-docs and graduate research assistants. This Web site has two main branches. The first contains our four annual data books of papillomavirus information, called Human Papillomaviruses: A Compilation and Analysis of Nucleic Acid and Amino Acid Sequences. and the second contains papillomavirus genetic sequence data. There is also a New Items location where we store the latest changes to the database or any other current news of interest. Besides the compendium, we also provide genetic sequence information for papilloma viruses and related cellular proteins. Each year they publish a compendium of papillomavirus information called Human Papillomaviruses: A Compilation and Analysis of Nucleic Acid and Amino Acid Sequences. which can now be downloaded from this Web site.

Proper citation: HPV Sequence Database (RRID:SCR_008154) Copy   

•   Source: SciCrunch Registry

http://www.animalgenome.org/pigs/nagrp.html

Database and resources on the pig genome.

Proper citation: U.S. Pig Genome Project (RRID:SCR_008151) Copy   

•   Source: SciCrunch Registry

http://csgr.pgml.uga.edu/

The objective of this project is to develop physical maps of the sorghum and rice genomes, based on BAC contigs that are cross-linked to each other and also to genetic maps and BAC islands for other large-genome crops and a library of ca. 50,000 expressed-sequence tags (EST''s) and corresponding cDNA clones, from diverse sorghum organs and developmental states. It also aims to improve understanding of genetic diversity and allelic richness that might be harbored ex situ (in gene banks) or in situ (in nature), and refine techniques for assesing allelic richness and Expedite data acquisition and utilization by a sound parnership between laboratory scientists and computational biologists. Specific goals of developing physical maps of sorghum and rice genomes include: -Enrich cross-links between sorghum and rice by mapping additional rice probes on sorghum. -Apply mapped DNA probes to macroarrays of sorghum, sugarcane, rice, and maize BACs. -Fingerprint 10x BAC libraries of Sorghum bicolor and S. propinquum. Libraries presently 3x and 6x respectively, to be expanded to 10x each. -Use fragment-matching (BAC-RF) method to determine locus-specificity in polyploids. - Contig assembly based on 1-3, plus rice BAC fingerprints generated under a separate Novartis project. -Evaluate methodology for rapid high-throughput assignment of new ESTs to BACs. -Conduct genomic sequencing in a region duplicated in both sorghum and arabidopsis. Selected BACs from sorghum(2), sugarcane, maize, rice, wheat. By improving the understanding of genetic diversity and allelic richness, the goal is to: -Sequence previously mapped sorghum DNA probes. -Discover & characterize 100 single nucleotide polymorphisms (SNPs) from cDNA markers. -Develop colorimetric high-throughput genotyping assays, and utilize to assess genetic diversity in geographically- and phenotypically-diverse sorghums. -Develop colorimetric high-throughput asssays for identifying phytochrome allelic variation, and apply these assays to a core collection representing a large set of genetic resources. -Support informatics group to streamline cataloging of DNA-level information relevant to large genetic resources collections. Lastly, the goals of expediting data acquisition and utilization include: -A new web-based resource for 3D-integration and visualization of structural and functional genomic data will be developed. -New sequence assembly and alignment software SABER (Sequence AssemBly in the presence of ERror), and PRIMAL(Practical RIgorous Multiple ALignment), will be evaluated with reference to existing standards (PHRED, PHRAP). -Specialized image processing and image analysis tools will be developed for acquistion and interpretation of qualitative and quantitative hybridization signals. To deal expeditiously with large volumes of data, parallel processing approaches will be investigated. Sponsors: * National Science Foundation (NSF) * National Sorghum Producers * University of Georgia Research Foundation (UGARF) * Georgia Research Alliance (GRA)

Proper citation: Comparative Saccharinae Genomics Resource (RRID:SCR_008153) Copy   

•   Source: SciCrunch Registry

http://genewindow.nci.nih.gov/

Software tool for pre- and post-genetic bioinformatics and analytical work, developed and used at the Core Genotyping Facility (CGF) at the National Cancer Institute. While Genewindow is implemented for the human genome and integrated with the CGF laboratory data, it stands as a useful tool to assist investigators in the selection of variants for study in vitro, or in novel genetic association studies. The Genewindow application and source code is publicly available for use in other genomes, and can be integrated with the analysis, storage, and archiving of data generated in any laboratory setting. This can assist laboratories in the choice and tracking of information related to genetic annotations, including variations and genomic positions. Features of GeneWindow include: -Intuitive representation of genomic variation using advanced web-based graphics (SVG) -Search by HUGO gene symbol, dbSNP ID, internal CGF polymorphism ID, or chromosome coordinates -Gene-centric display (only when a gene of interest is in view) oriented 5 to 3 regardless of the reference strand and adjacent genes -Two views, a Locus Overview, which varies in size depending on the gene or genomic region being viewed and, below it, a Sequence View displaying 2000 base pairs within the overview -Navigate the genome by clicking along the gene in the Locus Overview to change the Sequence View, expand or contract the genomic interval, or shift the view in the 5 or 3 direction (relative to the current gene) -Lists of available genomic features -Search for sequence matches in the Locus Overview -Genomic features are represented by shape, color and opacity with contextual information visible when the user moves over or clicks on a feature -Administrators can insert newly-discovered polymorphisms into the Genewindow database by entering annotations directly through the GUI -Integration with a Laboratory Information Management System (LIMS) or other databases is possible

Proper citation: GeneWindow (RRID:SCR_008183) Copy   

•   Source: SciCrunch Registry