Tools   Select Another Resource Report Type

http://www.sanger.ac.uk/resources/software/act/

A free tool for displaying pairwise comparisons between two or more DNA sequences. It can be used to identify and analyze regions of similarity and difference between genomes and to explore conservation of synteny, in the context of the entire sequences and their annotation. It is based on the software for Artemis, the genome viewer and annotation tool. ACT runs on UNIX, GNU/Linux, Macintosh and MS Windows systems. It can read complete EMBL and GENBANK entries or sequences in FASTA or raw format. Other sequence features can be in EMBL, GENBANK or GFF format.

Proper citation: ACT: Artemis Comparison Tool (RRID:SCR_004507) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/

Non-profit academic organization for research and services in bioinformatics. Provides freely available data from life science experiments, performs basic research in computational biology, and offers user training programme, manages databases of biological data including nucleic acid, protein sequences, and macromolecular structures. Part of EMBL.

Proper citation: European Bioinformatics Institute (RRID:SCR_004727) Copy   

•   Source: SciCrunch Registry

http://intermine.org/

An open source data warehouse system built for the integration and analysis of complex biological data that enables the creation of biological databases accessed by sophisticated web query tools. Parsers are provided for integrating data from many common biological data sources and formats, and there is a framework for adding data. InterMine includes a user-friendly web interface that works "out of the box" and can be easily customized for specific needs, as well as a powerful, scriptable web-service API to allow programmatic access to data.

Proper citation: InterMine (RRID:SCR_001772) Copy   

•   Source: SciCrunch Registry

http://neuronvisio.org/

A Graphical User Interface for NEURON simulator environment with 3D capabilities. Neuronvisio makes easy to select and investigate sections'''' properties and it offers easy integration with matplotlib for plotting the results. The geometry can be saved using NeuroML and the computational results in a customized and extensible HDF5 format; the results can then be reload in the software and analyzed in a later stage, without re-running the simulation. Featuring 3D visualization of the model with the possibility to change it runtime; creation of vectors to record any variables present in the section; pylab integration to plot directly the result of the simulation; exploration of the timecourse of any variable among time using a color coded scale; saving the results simulation for later analysis; automatic download and running of models in ModelDB.

Proper citation: NeuronVisio (RRID:SCR_006839) Copy   

•   Source: SciCrunch Registry

https://www.wtccc.org.uk/

Consortium of 50 research groups across the UK to harness the power of newly-available genotyping technologies to improve our understanding of the aetiological basis of several major causes of global disease. The consortium has gathered genotype data for up to 500,000 sites of genome sequence variation (single nucleotide polymorphisms or SNPs) in samples ascertained for the disease phenotypes. Analysis of the genome-wide association data generated has lead to the identification of many SNPs and genes showing evidence of association with disease susceptibility, some of which will be followed up in future studies. In addition, the Consortium has gained important insights into the technical, analytical, methodological and biological aspects of genome-wide association analysis. The core of the study comprised an analysis of 2,000 samples from each of seven diseases (type 1 diabetes, type 2 diabetes, coronary heart disease, hypertension, bipolar disorder, rheumatoid arthritis and Crohn's disease). For each disease, the case samples have been ascertained from sites widely distributed across Great Britain, allowing us to obtain considerable efficiencies by comparing each of these case populations to a common set of 3,000 nationally-ascertained controls also from England, Scotland and Wales. These controls come from two sources: 1,500 are representative samples from the 1958 British Birth Cohort and 1,500 are blood donors recruited by the three national UK Blood Services. One of the questions that the WTCCC study has addressed relates to the relative merits of these alternative strategies for the generation of representative population cohorts. Genotyping for this main Case Control study was conducted by Affymetrix using the (commercial) Affymetrix 500K chip. As part of this study a total of 17,000 samples were typed for 500,000 SNPs. There are two additional components to the study. First, the WTCCC award is part-funding a study of host resistance to infectious diseases in African populations. The same approach has been used to type 2,000 cases of tuberculosis (TB) and 2,000 cases of malaria, as well as 2,000 shared controls. As well as addressing diseases of major global significance, and extending WTCCC coverage into the area of infectious disease, the inclusion of samples of African origin has obvious benefits with respect to methodological aspects of genome-wide association analysis. Second, the WTCCC has, for four additional diseases (autoimmune thyroid disease, breast cancer, ankylosing spondylitis, multiple sclerosis), completed an analysis of 15,000 SNPs designed to represent a large proportion of the known non-synonymous coding SNPs across the genome. This analysis has been performed at the WTSI using a custom Infinium chip (Illumina). Data release The genotypic data of the control samples (1958 British Birth Cohort and UK Blood Service) and from seven diseases analyzed in the main study are now available to qualified researchers. Summary genotype statistics for these collections are available directly from the website. Access to the individual-level genotype data and summary genotype statistics is by application to the Consortium Data Access Committee (CDAC) and approval subject to a Data Access Agreement. WTCCC2: A further round of GWA studies were funded in April 2008. These include 15 WTCCC-collaborative studies and 12 independent studies be supported totaling approximately 120,000 samples. Many of the studies represent major international collaborative networks that have together assembled large sample collections. WTCCC2 will perform genome-wide association studies in 13 disease conditions: Ankylosing spondylitis, Barrett's oesophagus and oesophageal adenocarcinoma, glaucoma, ischaemic stroke, multiple sclerosis, pre-eclampsia, Parkinson's disease, psychosis endophenotypes, psoriasis, schizophrenia, ulcerative colitis and visceral leishmaniasis. WTCCC2 will also investigate the genetics of reading and mathematics abilities in children and the pharmacogenomics of statin response. Over 60,000 samples will be analyzed using either the Affymetrix v6.0 chip or the Illumina 660K chip. The WTCCC2 will also genotype 3,000 controls each from the 1958 British Birth cohort and the UK Blood Service control group, and the 6,000 controls will be genotyped on both the Affymetrix v6.0 and Illumina 1.2M chips. WTCCC3: The Wellcome Trust has provided support for a further round of GWA studies in January 2009. These include 5 WTCCC-collaborative studies to be carried out in WTCCC3 and 5 independent studies, across a range of diseases. Many of the studies represent major international collaborative networks that have together assembled large sample collections. WTCCC3 will perform genome-wide association studies in the following 4 disease conditions: primary biliary cirrhosis, anorexia nervosa, pre-eclampsia in UK subjects, and the interactions between donor and recipient DNA related to early and late renal transplant dysfunction. The WTCCC3 will also carry out a pilot in a study of the genetics of host control of HIV-1 infection. Over 40,000 samples will be analyzed using the Illumina 660K chip. The WTCCC3 will utilize the 6,000 control genotypes generated by the WTCCC2.

Proper citation: Wellcome Trust Case Control Consortium (RRID:SCR_001973) Copy   

•   Source: SciCrunch Registry

http://www.bwfund.org/

The Burroughs Wellcome Fund is an independent private foundation dedicated to advancing the biomedical sciences by supporting research and other scientific and educational activities. Within this broad mission, BWF has two primary goals: * To help scientists early in their careers develop as independent investigators * To advance fields in the basic biomedical sciences that are undervalued or in need of particular encouragement BWF''s financial support is channeled primarily through competitive peer-reviewed award programs. * BWF''s endowment: $586.8 million at the end of FY 2009 * BWF approved $26.4 million in grants during FY 2009 BWF makes grants primarily to degree-granting institutions on behalf of individual researchers, who must be nominated by their institutions. To complement these competitive award programs, BWF also makes grants to nonprofit organizations conducting activities intended to improve the general environment for science. A Board of Directors comprising distinguished scientists and business leaders governs BWF. BWF was founded in 1955 as the corporate foundation of the pharmaceutical firm Burroughs Wellcome Co. In 1993, a generous gift from the Wellcome Trust in the United Kingdom, enabled BWF to become fully independent from the company, which was acquired by Glaxo in 1995. BWF has no affiliation with any corporation.

Proper citation: Burroughs Wellcome Fund (RRID:SCR_005772) Copy   

•   Source: SciCrunch Registry

http://www.diffusiontools.com/documentation/poas.html

Software toolbox for SPM to denoise diffusion MRI data. Used for diffusion weighted magnetic resonance imaging data enhancement based on structural adaptive smoothing in both voxel space and diffusion-gradient space.Part of the ACID-toolbox.

Proper citation: POAS4SPM (RRID:SCR_010469) Copy   

•   Source: SciCrunch Registry

http://www.hipsci.org/

A UK national induced pluripotent stem (iPS) cell resource that will create and characterize more than 1000 human iPSCs from healthy and diseased tissue for use in cellular genetic studies. Between 2013 and 2016 they aim to generate iPS cells from over 500 healthy individuals and 500 individuals with genetic disease. They will then use these cells to discover how genomic variation impacts on cellular phenotype and identify new disease mechanisms. Strong links with NHS investigators will ensure that studies on the disease-associated cell lines will be linked to extensive clinical information. Further key features of the project are an open access model of data sharing; engagement of the wider clinical genetics community in selecting patient samples; and provision of dedicated laboratory space for collaborative cell phenotyping and differentiation.

Proper citation: HipSci (RRID:SCR_003909) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/mouseportal/

Database of mouse research resources at Sanger: BACs, targeting vectors, targeted ES cells, mutant mouse lines, and phenotypic data generated from the Institute''''s primary screen. The Wellcome Trust Sanger Institute generates, characterizes, and uses a variety of reagents for mouse genetics research. It also aims to facilitate the distribution of these resources to the external scientific community. Here, you will find unified access to the different resources available from the Institute or its collaborators. The resources include: 129S7 and C57BL6/J bacterial artificial chromosomes (BACs), MICER gene targeting vectors, knock-out first conditional-ready gene targeting vectors, embryonic stem (ES) cells with gene targeted mutations or with retroviral gene trap insertions, mutant mouse lines, and phenotypic data generated from the Institute''''s primary screen.

Proper citation: Sanger Mouse Resources Portal (RRID:SCR_006239) Copy   

•   Source: SciCrunch Registry

http://www.neuroconstruct.org/

Software for simulating complex networks of biologically realistic neurons, i.e. models incorporating dendritic morphologies and realistic cell membrane conductance, implemented in Java and generates script files for the NEURON and GENESIS simulators, with support for other simulation platforms (including PSICS and PyNN) in development. neuroConstruct is being developed in the Silver Lab in the Department of Neuroscience, Physiology and Pharmacology at UCL and uses the latest NeuroML specifications, including MorphML, ChannelML and NetworkML. Some of the key features of neuroConstruct are: Creation of networks of biologically realistic neurons, positioned in 3D space. Complex connectivity patterns between cell groups can be specified for the networks. Can import morphology files in GENESIS, NEURON, Neurolucida, SWC and MorphML format for inclusion in network models. Simulations can be run on the NEURON or GENESIS platforms. Cellular processes (synapses/channel mechanisms) can be imported from native script files or created in ChannelML. Recording of simulation data generated by the simulation and visualization/analysis of data. Stored simulation runs can be viewed and managed through the Simulation Browser interface.

Proper citation: neuroConstruct (RRID:SCR_007197) Copy   

•   Source: SciCrunch Registry

https://tristanic.github.io/isolde/

Software environment to ease task of building macromolecular models into low to medium resolution experimental maps. Physically realistic environment for model building into low-resolution electron-density maps. Can generate maps directly from crystallographic F/sigF data in MTZ format and automatically re-calculate them when model changes, and/or generate "static" maps from pre-calculated F/phi data.

Proper citation: ISOLDE (RRID:SCR_025577) Copy   

•   Source: SciCrunch Registry

https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/XTRACT

Software command line tool for automated tractography. Standardised protocols for automated tractography in human and macaque brain.

Proper citation: XTRACT (RRID:SCR_024933) Copy   

•   Source: SciCrunch Registry

http://www.genes2cognition.org/

A neuroscience research program that studies genes, the brain and behavior in an integrated manner, established to elucidate the molecular mechanisms of learning and memory, and shed light on the pathogenesis of disorders of cognition. Central to G2C investigations is the NMDA receptor complex (NRC/MASC), that is found at the synapses in the central nervous system which constitute the functional connections between neurons. Changes in the receptor and associated components are thought to be in a large part responsible for the phenomenon of synaptic plasticity, that may underlie learning and memory. G2C is addressing the function of synapse proteins using large scale approaches combining genomics, proteomics and genetic methods with electrophysiological and behavioral studies. This is incorporated with computational models of the organization of molecular networks at the synapse. These combined approaches provide a powerful and unique opportunity to understand the mechanisms of disease genes in behavior and brain pathology as well as provide fundamental insights into the complexity of the human brain. Additionally, Genes to Cognition makes available its biological resources, including gene-targeting vectors, ES cell lines, antibodies, and transgenic mice, generated for its phenotyping pipeline. The resources are freely-available to interested researchers.

Proper citation: Genes to Cognition: Neuroscience Research Programme (RRID:SCR_007121) Copy   

•   Source: SciCrunch Registry

http://www.port.ac.uk/research/exrc/

Supports researchers using Xenopus models. Researchers are encouraged to deposit Xenopus transgenic and mutant lines, Xenopus in situ hybridization probes, Xenopus specific antibodies and Xenopus expression clones with the Centre. EXRC staff perform quality assurance testing on these reagents and then make them available to researchers at cost. Supplies wild-type Xenopus, embryos, oocytes and Xenopus tropicalis fosmids.

Proper citation: European Xenopus Resource Center (RRID:SCR_007164) Copy   

•   Source: SciCrunch Registry

http://t1dbase.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 26,2019. In October 2016, T1DBase has merged with its sister site ImmunoBase (https://immunobase.org). Documented on March 2020, ImmunoBase ownership has been transferred to Open Targets (https://www.opentargets.org). Results for all studies can be explored using Open Targets Genetics (https://genetics.opentargets.org). Database focused on genetics and genomics of type 1 diabetes susceptibility providing a curated and integrated set of datasets and tools, across multiple species, to support and promote research in this area. The current data scope includes annotated genomic sequences for suspected T1D susceptibility regions; genetic data; microarray data; and global datasets, generally from the literature, that are useful for genetics and systems biology studies. The site also includes software tools for analyzing the data.

Proper citation: T1DBase (RRID:SCR_007959) Copy   

•   Source: SciCrunch Registry

http://rfam.xfam.org/

The Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down into three broad functional classes: Non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Typically these functional RNAs often have a conserved secondary structure which may be better preserved than the RNA sequence. The CMs used to describe each family are a slightly more complicated relative of the profile hidden Markov models (HMMs) used by Pfam. CMs can simultaneously model RNA sequence and the structure in an elegant and accurate fashion. Rfam is also available via FTP. You can find data in Rfam in various ways... * Analyze your RNA sequence for Rfam matches * View Rfam family annotation and alignments * View Rfam clan details * Query Rfam by keywords * Fetch families or sequences by NCBI taxonomy * Enter any type of accession or ID to jump to the page for a Rfam family, sequence or genome

Proper citation: Rfam (RRID:SCR_007891) Copy   

•   Source: SciCrunch Registry

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

An international leader in genetics, genomics and structural biology, and research institute of the Nuffield Department of Medicine at the University of Oxford, whose objective is to extend our understanding on how genetic inheritance makes us who we are in order to gain a clearer insight into mechanisms of health and disease. Looking across all three billion letters of the human genetic code, they aim to pinpoint variant spellings and discover how they increase or decrease an individual's risk of falling ill. They collaborate with research teams across the world on a number of large-scale studies in these areas.

Proper citation: Wellcome Trust Centre for Human Genetics (RRID:SCR_003307) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/pride/

Centralized, standards compliant, public data repository for proteomics data, including protein and peptide identifications, post-translational modifications and supporting spectral evidence. Originally it was developed to provide a common data exchange format and repository to support proteomics literature publications. This remit has grown with PRIDE, with the hope that PRIDE will provide a reference set of tissue-based identifications for use by the community. The future development of PRIDE has become closely linked to HUPO PSI. PRIDE encourages and welcomes direct user submissions of protein and peptide identification data to be published in peer-reviewed publications. Users may Browse public datasets, use PRIDE BioMart for custom queries, or download the data directly from the FTP site. PRIDE has been developed through a collaboration of the EMBL-EBI, Ghent University in Belgium, and the University of Manchester.

Proper citation: Proteomics Identifications (PRIDE) (RRID:SCR_003411) Copy   

•   Source: SciCrunch Registry

http://images.wellcome.ac.uk/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023.Digital collection of images, with themes ranging from medical and social history to contemporary healthcare and biomedical science. The collection contains historical images from the Wellcome Library collections, Tibetan Buddhist paintings, ancient Sanskrit manuscripts written on palm leaves, beautifully illuminated Persian books and much more. The Biomedical Collection holds over 40 000 high-quality images from the clinical and biomedical sciences. Selected from the UK''s leading teaching hospitals and research institutions, it covers disease, surgery, general healthcare, sciences from genetics to neuroscience including the full range of imaging techniques. They are always looking for new high quality biomedical images from scientific researchers, clinical photographers and artists in any field of science or medicine. As a contributor you retain your original material and copyright, and receive commission and full credit each time your images are used. The annual Wellcome Images awards (previously known as Biomedical Images Awards) reward contributors for their outstanding work and winners are chosen by a panel of experts. The resulting public exhibitions are always extremely popular and receive widespread acclaim. All images on the Wellcome Images site are available free for use in: * private study and non-commercial research * examination papers * criticism and review, this applies only where there are no multiple copies made * theses submitted by a student at a higher or further education institution for the purposes of securing a degree * personal use by private individuals

Proper citation: Wellcome Images (RRID:SCR_004181) Copy   

•   Source: SciCrunch Registry

http://www.ddduk.org/

The Deciphering Developmental Disorders (DDD) study aims to find out if using new genetic technologies can help doctors understand why patients get developmental disorders. To do this we have brought together doctors in the 23 NHS Regional Genetics Services throughout the UK and scientists at the Wellcome Trust Sanger Institute, a charitably funded research institute which played a world-leading role in sequencing (reading) the human genome. The DDD study involves experts in clinical, molecular and statistical genetics, as well as ethics and social science. It has a Scientific Advisory Board consisting of scientists, doctors, a lawyer and patient representative, and has received National ethical approval in the UK. Over the next few years, we are aiming to collect DNA and clinical information from 12,000 undiagnosed children in the UK with developmental disorders and their parents. The results of the DDD study will provide a unique, online catalogue of genetic changes linked to clinical features that will enable clinicians to diagnose developmental disorders. Furthermore, the study will enable the design of more efficient and cheaper diagnostic assays for relevant genetic testing to be offered to all such patients in the UK and so transform clinical practice for children with developmental disorders. Over time, the work will also improve understanding of how genetic changes cause developmental disorders and why the severity of the disease varies in individuals. The Sanger Institute will contribute to the DDD study by performing genetic analysis of DNA samples from patients with developmental disorders, and their parents, recruited into the study through the Regional Genetics Services. Using microarray technology and the latest DNA sequencing methods, research teams will probe genetic information to identify mutations (DNA errors or rearrangements) and establish if these mutations play a role in the developmental disorders observed in patients. The DDD initiative grew out of the groundbreaking DECIPHER database, a global partnership of clinical genetics centres set up in 2004, which allows researchers and clinicians to share clinical and genomic data from patients worldwide. The DDD study aims to transform the power of DECIPHER as a diagnostic tool for use by clinicians. As well as improving patient care, the DDD team will empower researchers in the field by making the data generated securely available to other research teams around the world. By assembling a solid resource of high-quality, high-resolution and consistent genomic data, the leaders of the DDD study hope to extend the reach of DECIPHER across a broader spectrum of disorders than is currently possible.

Proper citation: Deciphering Developmental Disorders (RRID:SCR_006171) Copy   

•   Source: SciCrunch Registry