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An information extracting and processing package for biological literature that can be used online or installed locally via a downloadable software package, http://www.textpresso.org/downloads.html Textpresso's two major elements are (1) access to full text, so that entire articles can be searched, and (2) introduction of categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or describe one (e.g., methods, etc). A search engine enables the user to search for one or a combination of these categories and/or keywords within an entire literature. The Textpresso project serves the biological and biomedical research community by providing: * Full text literature searches of model organism research and subject-specific articles at individual sites. Major elements of these search engines are (1) access to full text, so that the entire content of articles can be searched, and (2) search capabilities using categories of biological concepts and classes that relate two objects (e.g., association, regulation, etc.) or identify one (e.g., cell, gene, allele, etc). The search engines are flexible, enabling users to query the entire literature using keywords, one or more categories or a combination of keywords and categories. * Text classification and mining of biomedical literature for database curation. They help database curators to identify and extract biological entities and facts from the full text of research articles. Examples of entity identification and extraction include new allele and gene names and human disease gene orthologs; examples of fact identification and extraction include sentence retrieval for curating gene-gene regulation, Gene Ontology (GO) cellular components and GO molecular function annotations. In addition they classify papers according to curation needs. They employ a variety of methods such as hidden Markov models, support vector machines, conditional random fields and pattern matches. Our collaborators include WormBase, FlyBase, SGD, TAIR, dictyBase and the Neuroscience Information Framework. They are looking forward to collaborating with more model organism databases and projects. * Linking biological entities in PDF and online journal articles to online databases. They have established a journal article mark-up pipeline that links select content of Genetics journal articles to model organism databases such as WormBase and SGD. The entity markup pipeline links over nine classes of objects including genes, proteins, alleles, phenotypes, and anatomical terms to the appropriate page at each database. The first article published with online and PDF-embedded hyperlinks to WormBase appeared in the September 2009 issue of Genetics. As of January 2011, we have processed around 70 articles, to be continued indefinitely. Extension of this pipeline to other journals and model organism databases is planned. Textpresso is useful as a search engine for researchers as well as a curation tool. It was developed as a part of WormBase and is used extensively by C. elegans curators. Textpresso has currently been implemented for 24 different literatures, among them Neuroscience, and can readily be extended to other corpora of text.
Proper citation: Textpresso (RRID:SCR_008737) Copy
http://vortex.cs.wayne.edu/projects.htm#OE2GO
Onto-Express is a web-based tool in the Onto-Tools suite that performs automated function profiling for a list of differentially expressed genes. However, Onto-Express does not support functional profiling for the organisms that do not have annotations in public domain, or use of custom (i.e. user-defined) ontologies. This limitation is also true for most of the other existing tools for functional profiling, which means that researchers working with uncommon organisms and/or new annotations or ontologies may be forced to construct such profiles manually. Onto-Express To Go (OE2GO) is a new tool added to the Onto-Tools ensemble to address these issues. OE2GO is built on top of OE to leverage its existing functionality. In OE2GO, the users now have an option to use either the Onto-Tools database as a source of functional annotations or provide their own annotations in a separate file. Currently, OE2GO supports annotation file in the Gene Ontology format. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: Onto-Express To Go (OE2GO) (RRID:SCR_008854) Copy
We aim to facilitate the pathway for access, storage, use and transfer of human organs, cells and tissue between clinical centers within UCL Partners, academic groups in UCL, other universities, hospitals, medical researcher and biotechnology companies, to enhance the ability for researchers to access the materials they need. Alongside this, researchers will be able to exchange information and access guides on regulatory, ethics and practical issues concerning access, transfer and use of this type of material. These guides will be video and documents format, based on talks at organized events given by experts in the relevant fields. All of this information will be accessible on a website that seeks to link groups within UCL and attract attention from the wider world through social media and expansion of existing contacts. Our vision is to develop a centralized human tissue provision and utilization service for academic and commercial researchers UCL has the highest concentration of biomedical researchers in Europe. As part of this, UCL has numerous licensed biobanks and is associated with many research intensive hospitals in North London. The role of a biobank is to prepare and hold human tissue samples in for use by medical researchers to help delivery new treatments. Hospitals can also provide human tissue for research by utilizing waste human tissue taken as part of surgery or diagnostic procedures, but is normally incinerated. The researchers using the human tissue could be working within academic laboratories in UK universities and institutions or as part of commercial companies. Researchers currently cannot easily access human tissue to meet the demands of their research, often due to the long ethical, regulatory and contractual processes. However, with the enormous UCL biobanking and research Hospital resources, UCL could be a leading academic institution in providing human tissue for medical research within the UK and internationally. Our vision is to develop a centralized human tissue provision and utilization service for academic and commercial researchers. This relies on creating an overarching infrastructure, to consolidate information on disparate human tissue resources around UCL, and (where possible) gain centralized ethical and regulatory and contractual approval for use of the tissue. Funding the infrastructure will rely on a cost recovery model for a per sample basis. As a result the time needed to obtain tissue for research will be dramatically reduced, whilst providing a simple costing model for obtaining human tissue. This will make human tissue procurement much more efficient for end users.
Proper citation: Tissue Access for Patient Benefit (RRID:SCR_008853) Copy
http://www.openmicroscopy.org/site
Open tools to support data management for biological light microscopy produced by a multi-site collaborative effort among academic laboratories and a number of commercial entities. Designed to interact with existing commercial software, all OME formats and software are free, and all OME source code is available under the GNU General public license or through commercial license from Glencoe Software. OME is developed as a joint project between research-active laboratories at the Dundee, NIA Baltimore, and Harvard Medical School and LOCI. In addition, OME has active collaborations with many imaging and informatics groups. While many other applications could use OME''s architecture and design, their specific implementation is focused on biological and biomedical imaging. Those interested in applying OME''s technology to other applications should contact the developers. OME work is divided into several different standards and software projects: * Bio-Formats: A Java-based library for reading and writing over 90 microscopy file formats. * OMERO Software: The Java-based OMERO software project, which currently includes tools for storing, visualizing, managing, and annotating microscopic images and metadata. * OME-XML & OME-TIFF: The OME-XML and OME-TIFF file format specifications, which are open file formats for sharing microscope image data. * OME Server: This was the original OME server project which has now ended and is a legacy product. It implements image-based analysis of cellular dynamics and image-based screening of cellular localization or phenotypes, and included a fully developed version of the 2003 version of OME-XML Schema language.
Proper citation: OME - Open Microscopy Environment (RRID:SCR_008849) Copy
http://www.nitrc.org/projects/dfbidb/
A suite of tools for efficient management of neuroimaging project data. Specifically, DFBIdb was designed to allow users to quickly perform routine management tasks of sorting, archiving, exploring, exporting and organising raw data. DFBIdb was implemented as a collection of Python scripts that maintain a project-based, centralised database that is based on the XCEDE 2 data model. Project data is imported from a filesystem hierarchy of raw files, which is an often-used convention of imaging devices, using a single script that catalogues meta-data into a modified XCEDE 2 data model. During the import process data are reversibly anonymised, archived and compressed. The import script was designed to support multiple file formats and features an extensible framework that can be adapted to novel file formats. Graphical user interfaces are provided for data exploration. DFBIdb includes facilities to export, convert and organise customisable subsets of project data according to user-specified criteria.
Proper citation: DFBIdb (RRID:SCR_009456) Copy
http://www.nitrc.org/projects/diamond/
Software to: view dicom files and assemble them into 3D volumes. View and convert between Analyze, Nifti, and Interfile. Classify and organize dicoms and 3D volumes using metadata. Search and report on a collection of scans.
Proper citation: DIAMOND (RRID:SCR_009457) Copy
https://CRAN.R-project.org/package=gma
Software package to perform Granger mediation analysis for time series. Includes single level GMA model and two-level GMA model, for time series with hierarchically nested structure.
Proper citation: GMA (RRID:SCR_009212) Copy
http://www.nitrc.org/projects/cbs-tools/
A fully automated processing pipeline for cortical analysis of structural MR images at a resolution of up to 400������m, including skull stripping, whole brain segmentation, cortical extraction, surface inflation and mapping, as well as dedicated tools for profile estimation across the cortical thickness. The tools are released as a set of plug-ins for the MIPAV software package and the JIST pipeline environment. They are therefore cross-platform and compatible with a wide variety of file formats.
Proper citation: CBS High-Res Brain Processing Tools (RRID:SCR_009452) Copy
http://www.nitrc.org/projects/ccseg/
An open-source C++-based application that allows automatic as well as user-interactive segmentation of the Corpus Callosum. Via a Qt-based graphical user interface, CCSeg also performs semi-automatic segmentation.
Proper citation: CCSeg - Corpus Callosum Segmentation (RRID:SCR_009453) Copy
http://crezoo.crt-dresden.de/crezoo/
Database of helpful set of CreERT2 driver lines expressing in various regions of the developing and adult zebrafish. The lines have been generated via the insertion of a mCherry-T2A-CreERT2 in a gene trap approach or by using promoter fragments driving CreERT2. You can search the list of all transgenic lines or single entries by insertions (gene) or expression patterns (anatomy/region). In most cases the CreERT2 expression profile using in situ hybridization at 24 hpf and 48 hpf is shown, but also additional information (e.g. mCherry or CreERT2 expression at adult stages, transactivation of a Cre-dependent reporter line) is displayed. Currently, not all insertions have been mapped to a genomic location but the database will be regularly updated adding newly generated insertions and mapping information. Your help in improving and broadening the database by giving your opinion or knowledge of expression patterns is highly appreciated.
Proper citation: CreZoo (RRID:SCR_008919) Copy
http://clipserve.clip.ubc.ca/topfind
An integrated knowledgebase focused on protein termini, their formation by proteases and functional implications. It contains information about the processing and the processing state of proteins and functional implications thereof derived from research literature, contributions by the scientific community and biological databases. It lists more than 120,000 N- and C-termini and almost 10,000 cleavages. TopFIND is a resource for comprehensive coverage of protein N- and C-termini discovered by all available in silico, in vitro as well as in vivo methodologies. It makes use of existing knowledge by seamless integration of data from UniProt and MEROPS and provides access to new data from community submission and manual literature curating. It renders modifications of protein termini, such as acetylation and citrulination, easily accessible and searchable and provides the means to identify and analyse extend and distribution of terminal modifications across a protein. The data is presented to the user with a strong emphasis on the relation to curated background information and underlying evidence that led to the observation of a terminus, its modification or proteolytic cleavage. In brief the protein information, its domain structure, protein termini, terminus modifications and proteolytic processing of and by other proteins is listed. All information is accompanied by metadata like its original source, method of identification, confidence measurement or related publication. A positional cross correlation evaluation matches termini and cleavage sites with protein features (such as amino acid variants) and domains to highlight potential effects and dependencies in a unique way. Also, a network view of all proteins showing their functional dependency as protease, substrate or protease inhibitor tied in with protein interactions is provided for the easy evaluation of network wide effects. A powerful yet user friendly filtering mechanism allows the presented data to be filtered based on parameters like methodology used, in vivo relevance, confidence or data source (e.g. limited to a single laboratory or publication). This provides means to assess physiological relevant data and to deduce functional information and hypotheses relevant to the bench scientist. TopFIND PROVIDES: * Integration of protein termini with proteolytic processing and protein features * Displays proteases and substrates within their protease web including detailed evidence information * Fully supports the Human Proteome Project through search by chromosome location CONTRIBUTE * Submit your N- or C-termini datasets * Contribute information on protein cleavages * Provide detailed experimental description, sample information and raw data
Proper citation: TopFIND (RRID:SCR_008918) Copy
http://bioinformatics.fccc.edu/software/OpenSource/FGDP/FGDP.shtml
A Java-based, Microarray or Genechip data analysis system.
Proper citation: FGDP (RRID:SCR_008910) Copy
http://code.google.com/p/elk-reasoner/
ELK is an ontology reasoner with the goal of supporting the OWL 2 EL profile. ELK is a specialized reasoner for the lightweight ontology language OWL EL. The practical utility of ELK is in its combination of high performance and comprehensive support for language features. At its core, ELK employs a consequence-based reasoning engine that can take advantage of multi-core and multi-processor systems. A modular architecture allows ELK to be used as a stand-alone application, Protege plug-in, or programming library (either with or without the OWL API).
Proper citation: elk-reasoner (RRID:SCR_008913) Copy
PDBj (Protein Data Bank Japan) maintains a centralized PDB archive of macromolecular structures and provides integrated tools, in collaboration with the RCSB, the BMRB in USA and the PDBe in EU.
Proper citation: PDBj - Protein Data Bank Japan (RRID:SCR_008912) Copy
http://www.nitrc.org/projects/brainsolution/
A collection of tools for MRI T1 brain image segmentation in the Windows environment. It helps construct a complete pipeline with necessary preprocessing and postprocessing procedures besides brainparser, the core program of our fast brain segmentation. The execution of the whole pipeline can be completed in 2 hours with good segmentation results. Execution requires: FSL
Proper citation: BrainSolution (RRID:SCR_009447) Copy
Center mission is to advance medical and biological research by providing the scientific community with standardized, high quality metabolic and physiologic phenotyping services for mouse models of diabetes, diabetic complications, obesity and related disorders.
Proper citation: National Mouse Metabolic Phenotyping Centers (RRID:SCR_008997) Copy
http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/09915/version/3
A collection of data that describes and identifies predictors of mortality, hospitalization, and placement in long-term care facilities and investigates risk factors for chronic diseases and loss of functioning. The EPESE project consisted of baseline and annual follow-up surveys on approximately 14,000 noninstitutionalized persons aged 65 and older in four geographically-defined communities: East Boston, Massachusetts; Iowa and Washington counties, Iowa; New Haven, Connecticut (started in 1982-1983); and a five-county-wide region in north-central North Carolina (started in 1986). Half of the participants in the North Carolina EPESE are African-American. The baseline data cover demographic characteristics (age, sex, race, height, weight, income, education, marital status, number of children, employment, and religion); social and physical functioning; chronic conditions; related health problems; health habits; self-reported use of dental, hospital, and nursing home services. More detailed descriptions of the Iowa and North Carolina surveys follow in this document (Iowa 65+ Rural Health Study and PHSE Ten-Year Follow-up of North Carolina EPESE). Data Availability: Data from the baseline and the first 6 years of follow-up are available as ICPSR Study No. 9915. Information from death certificates obtained for deaths occurring in the first 6 years of follow-up is also available. * Dates of Study: 1981-1993 * Study Features: Longitudinal, Minority Oversamples, Anthropometric Measures * Sample Size: ** 1981: 14,458 (Baseline) ** 1982: 14,070 (First follow-up) ** 1983: 13,382 (Second follow-up) ** 1984: 12,381 (Third follow-up) ** 1985: 11,657 (Fourth follow-up) ** 1986: 10,998 (Fifth follow-up) ** 1987: 9,998 (Sixth follow-up) Link * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/09915
Proper citation: Established Populations for Epidemiologic Studies of the Elderly (RRID:SCR_008909) Copy
An Antibody supplier, Core facility
Proper citation: Biomatik (RRID:SCR_008944) Copy
https://www.beckmancoulter.com/
An Organization portal, Material service resource, Antibody supplier, Instrument supplier
Proper citation: Beckman Coulter (RRID:SCR_008940) Copy
http://www.nitrc.org/projects/frat/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on November 05, 2013. It has been superseeded by the CALATK, available here http://www.calatk.org c++ libraries and applications for performing fluid registration based operations on 2D and 3D images. The registration method is based on the large displacement diffeomorphic mapping (LDDM) registration method and implements discretized fluid registration. This registration method is then applied to time series analysis, cross-sectional atlas building, and longitudinal atlas building. The individual tool components are: * LDDM: Fluid registration between two images. * TimeSeries: Time series analysis of longitudinal data for a single subject. * AtlasBuilder: Cross-sectional atlas building for a population of images. * LongitudinalAtlasBuilder: Longitudinal atlas building for a population of subjects, each with a longitudinal data set. * FRATUtils: A collection of utility functions for working with volumes and time series files
Proper citation: Fluid Registration and Atlas Toolkit (RRID:SCR_009478) Copy
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