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http://www.roslin.ed.ac.uk/about-roslin/
The world''s largest collection of tick cell lines, enabling scientists to carry out advanced research. This biobank is establishing a collection of all the continuous cell lines derived from ixodid and argasid ticks of medical and veterinary importance available worldwide now and in future. Ticks are blood feeding arthropods which transmit many human and animal diseases. Research into prevention and cure of these diseases, which are caused by viruses, bacteria and protozoa, is greatly assisted by the use of cell culture systems which enable study of both how tick cells function, and how and why ticks transmit these disease-causing pathogens. Cell lines will always be shipped to recipient laboratories as growing cultures, since we cannot guarantee successful resuscitation of frozen stabilates. Tick cells in culture can tolerate the range of temperatures experienced during transit by air for up to a week. Training: We will provide training in tick cell line care and maintenance. This is an essential component of successful transfer of tick cells to, and their establishment in, laboratories with little or no previous experience of tick cell culture. Recipient scientists (preferably the person who will actually look after the cells) can visit the biobank for between 2 days and 2 weeks, depending on their level of previous experience, to be trained in the specific approach and methods for tick cell cultivation. Establishment of new cell lines: In response to requests and on receipt of suitable starting material (engorged female or moulting nymphal ticks), we will attempt to establish new cell lines from tick species or strains which are not already represented in the collection. Deposition of new tick cell lines: We invite researchers anywhere in the world who have established new tick cell lines to deposit samples for safekeeping free of charge and, if requested, for distribution alongside the existing biobank portfolio.
Proper citation: Roslin Wellcome Trust Tick Cell Biobank (RRID:SCR_004228) Copy
A long-term health research project which follows pregnant women and their offspring in a continuous health and developmental study. More than 14,000 mothers enrolled during pregnancy in 1991 and 1992, and the health and development of their children has been followed in great detail. The ALSPAC families have provided a vast amount of genetic and environmental information over the years which can be made available to researchers globally.
Proper citation: ALSPAC (RRID:SCR_007260) Copy
http://www.ucl.ac.uk/ploras#annotations:QXuC2C7REeaxtw-aEPo07Q
A research project investigating the difficulties of recovering language after stroke (aphasia). The overall aim of the study is to give future stroke survivors accurate predictions of their aphasia recovery by creating clinical tools and discerning why some patients recover from aphasia better than others.
Proper citation: Predicting Language Outcome and Recovery After Stroke (PLORAS) (RRID:SCR_014498) Copy
Facility provides diverse range of equipment, expertise and training in field of biochemistry, molecular, structural and cellular biology. Facility consists of several research laboratories and support areas.
Proper citation: University College London Darwin Research Core Facility (RRID:SCR_026345) Copy
http://sbcb.bioch.ox.ac.uk/kdb/
A Database of Potassium Ion Channel Homology Models & Molecular Dynamics Simulations.
Proper citation: Potassium Channel Database (RRID:SCR_011960) Copy
https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/TBSS
Software tool to improve sensitivity, objectivity and interpretability of analysis of multi-subject diffusion imaging studies.
Proper citation: Tract Based Spatial Statistics (RRID:SCR_024932) Copy
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
https://brainlife.io/docs/using_ezBIDS/
Web-based BIDS conversion tool to convert neuroimaging data and associated metadata to BIDS standard. Guided standardization of neuroimaging data interoperable with major data archives and platforms.
Proper citation: ezBIDS (RRID:SCR_025563) Copy
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
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
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
http://caps.ncbs.res.in/3dswap/index.html
Curated knowledegbase of protein structures that are reported to be involved in 3-dimensional domain swapping. 3DSwap provides literature curated information and structure related information about 3D domain swapping in proteins. Information about swapping, hinge region, swapped region, extent of swapping, etc. are extracted from original research publications after extensive literature curation.
Proper citation: 3DSwap (RRID:SCR_004133) Copy
http://www.hgsc.bcm.tmc.edu/content/hapmap-3-and-encode-3
Draft release 3 for genome-wide SNP genotyping and targeted sequencing in DNA samples from a variety of human populations (sometimes referred to as the HapMap 3 samples). This release contains the following data: * SNP genotype data generated from 1184 samples, collected using two platforms: the Illumina Human1M (by the Wellcome Trust Sanger Institute) and the Affymetrix SNP 6.0 (by the Broad Institute). Data from the two platforms have been merged for this release. * PCR-based resequencing data (by Baylor College of Medicine Human Genome Sequencing Center) across ten 100-kb regions (collectively referred to as ENCODE 3) in 712 samples. Since this is a draft release, please check this site regularly for updates and new releases. The HapMap 3 sample collection comprises 1,301 samples (including the original 270 samples used in Phase I and II of the International HapMap Project) from 11 populations, listed below alphabetically by their 3-letter labels. Five of the ten ENCODE 3 regions overlap with the HapMap-ENCODE regions; the other five are regions selected at random from the ENCODE target regions (excluding the 10 HapMap-ENCODE regions). All ENCODE 3 regions are 100-kb in size, and are centered within each respective ENCODE region. The HapMap 3 and ENCORE 3 data are downloadable from the ftp site.
Proper citation: HapMap 3 and ENCODE 3 (RRID:SCR_004563) Copy
A database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).
Proper citation: Pfam (RRID:SCR_004726) Copy
http://www.compbio.dundee.ac.uk/gotcha/gotcha.php
GOtcha provides a prediction of a set of GO terms that can be associated with a given query sequence. Each term is scored independently and the scores calibrated against reference searches to give an accurate percentage likelihood of correctness. These results can be displayed graphically. Why is GOtcha different to what is already out there and why should you be using it? * GOtcha uses a method where it combines information from many search hits, up to and including E-values that are normally discarded. This gives much better sensitivity than other methods. * GOtcha provides a score for each individual term, not just the leaf term or branch. This allows the discrimination between confident assignments that one would find at a more general level and the more specific terms that one would have lower confidence in. * The scores GOtcha provides are calibrated to give a real estimate of correctness. This is expressed as a percentage, giving a result that non-experts are comfortable in interpreting. * GOtcha provides graphical output that gives an overview of the confidence in, or potential alternatives for, particular GO term assignments. The tool is currently web-based; contact David Martin for details of the standalone version. Platform: Online tool
Proper citation: GOtcha (RRID:SCR_005790) Copy
http://www.ebi.ac.uk/expressionprofiler/
THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.
Proper citation: Expression Profiler (RRID:SCR_005821) Copy
http://www.ebi.ac.uk/thornton-srv/databases/FunTree/
FunTree provides a range of data resources to detect the evolution of enzyme function within distant structurally related clusters within domain super families as determined by CATH. To access the resource enter a specific CATH superfamily code or search for a structure / sequence / function (either via a EC code or KEGG ligand / reaction ID, PDB ID or UniProtKB ID). Or browse the resource via superfamily / function / structure / metabolites & reactions via the menu on the left panel. FunTree is a new resource that brings together sequence, structure, phylogenetic, chemical and mechanistic information for structurally defined enzyme superfamilies. Gathering together this range of data into a single resource allows the investigation of how novel enzyme functions have evolved within a structurally defined superfamily as well as providing a means to analyse trends across many superfamilies. This is done not only within the context of an enzyme''''s sequence and structure but also the relationships of their reactions. Developed in tandem with the CATH database, it currently comprises 276 superfamilies covering 1800 (70%) of sequence assigned enzyme reactions. Central to the resource are phylogenetic trees generated from structurally informed multiple sequence alignments using both domain structural alignments supplemented with domain sequences and whole sequence alignments based on commonality of multi-domain architectures. These trees are decorated with functional annotations such as metabolite similarity as well as annotations from manually curated resources such the catalytic site atlas and MACiE for enzyme mechanisms.
Proper citation: FunTree (RRID:SCR_006014) Copy
https://vertebrate.genenames.org/
Software resource for vertebrate gene nomenclature. Database of gene symbols. Coordinates with vertebrate nomenclature committees, MGNC (mouse), RGNC (rat), CGNC (chicken), AGNC (Anole green lizard), XNC (Xenopus frog) and ZNC (zebrafish), to ensure genes are named in line with their human homologs.
Proper citation: VGNC (RRID:SCR_017514) Copy
http://www.sanger.ac.uk/cgi-bin/teams/team30/arnie
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1,2023. Database that integrates the extracellular protein interaction network generated in our lab using AVEXIS technology with spatiotemporal expression patterns for all genes in the network. The tool allows users to browse the network by clicking on individual proteins, or by specifying the spatiotemporal parameters. Clicking on connector lines will allow users to compare stage-matched expression patterns for genes encoding interacting proteins. Additionally, users can rapidly search for their genes in the network using the BLAST server provided.
Proper citation: ARNIE (RRID:SCR_000514) Copy
http://www.nactem.ac.uk/biolexicon/
A large-scale English terminological database that contains over 2.2.M lexical entries (3.3M semantic relations), terminological variants and rich linguistic information (subcategorization frames) which supports text mining systems. It is primarily intended to support text mining and information retrieval in the biomedical domain. The BioLexicon provides specific information to help determine the relevant facts to be extracted. BioLexicon is available in a relational database format (MySQL dump format) and it adheres to the EAGLES/ISO standards for lexical resources.
Proper citation: BioLexicon (RRID:SCR_000589) Copy
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