Curator Dashboard

THIS RESOURCE IS NO LONGER IN SERVICE. Datasets described in the manuscript: "Global Epigenomic Reconfiguration During Mammalian Brain Development" (Science, 2013 - DOI: 10.1126/science.1237905. This study provides genome-wide composition, patterning, cell specificity, and dynamics of DNA methylation at single-base resolution in human and mouse frontal cortex throughout their lifespan. Widespread methylome reconfiguration occurs during fetal to young adult development, coincident with synaptogenesis.

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• SciCrunch
• 14 years ago - by Anonymous

Software that estimates expression at transcript-level resolution and controls for variability evident across replicate libraries.

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• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Friend is a bioinformatics application designed for simultaneous analysis and visualization of multiple structures and sequences of proteins and/or DNA/RNA. The application provides basic functionalities such as: structure visualization with different rendering and coloring, sequence alignment, and simple phylogeny analysis, along with a number of extended features to perform more complex analyses of sequence structure relationships, including: structural alignment of proteins, investigation of specific interaction motifs, studies of protein-protein and protein-DNA interactions, and protein super-families. Friend is also useful for the functional annotation of proteins, protein modeling, and protein folding studies. Friend provides three levels of usage; 1) an extensive GUI for a scientist with no programming experience, 2) a command line interface for scripting for a scientist with some programming experience, and 3) the ability to extend Friend with user written libraries for an experienced programmer. The application is linked and communicates with local and remote sequence and structure databases.

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• SciCrunch
• 17 years ago - by Anonymous

An integrated and flexible software package for processing of DTI data, and in general for the correction of diffusion weighted images to be used for DTI and potentially for high angular resolution diffusion imaging (HARDI) analysis. It can be run on both Linux and Mac platforms. It is composed of two modules named DIFF PREP and DIFF CALC. * DIFF_PREP - software for image resampling, motion, eddy current distortion and susceptibility induced EPI distortion corrections, and for re-orientation of data to a common space * DIFF_CALC - software for tensor fitting, error analysis, color map visualization and ROI analysis In addition, TORTOISE contains additional Utilities, such as a tool for the analysis of multi-center phantom data.

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• SciCrunch
• 14 years ago - by Anonymous

A Python-based open source toolkit for magnetic resonance connectome mapping, data management, sharing, visualization and analysis. The toolkit includes the connectome mapper (a full DMRI processing pipeline), a new file format for multi modal data and metadata, and a visualization application.

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• SciCrunch
• 14 years ago - by Anonymous

A graphical toolbox developed in Matlab for exploratory diffusion (tensor) MRI and fiber tractography. It includes diffusion reconstruction approaches, analysis and visualization tools for fiber tractography, atlas based segmentation, and connectivity networks. It also provides a wide range of quality assessment and pre-processing tools. Main features: * Visualization of scalar and vector maps of various diffusion tensor properties * Display of principal diffusion vectors, cuboids, and ellipsoids with several color-encodings * Deterministic (streamline) and 'probabilistic' (wild-bootstrap) fiber tractography * Clustering of fiber tracts * Data quality assessment tools * HARDI reconstructions (Q-ball and spherical deconvolution imaging) * Tract-specific measurements * Tract-segment analysis * Motion / distortion correction (with B-matrix rotation!) * Other cool stuff... (see publication link)

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• SciCrunch
• 14 years ago - by Anonymous

A spatial normalization and atlas construction toolkit optimized for examining white matter morphometry using DTI data with special care taken to respect the tensorial nature of the data. It implements a state-of-the-art registration algorithm that drives the alignment of white matter (WM) tracts by matching the orientation of the underlying fiber bundle at each voxel. The algorithm has been shown to both improve WM tract alignment and to enhance the power of statistical inference in clinical settings. A 2011 study published in NeuroImage ranks DTI-TK the top-performing tool in its class. Key features include: * open standard-based file IO support: NIfTI format for scalar, vector and tensor image volumes * tool chains for manipulating tensor image volumes: resampling, smoothing, warping, registration & visualization * pipelines for WM morphometry: spatial normalization & atlas construction for population-based studies * built-in cluster-computing support: support for open source Sun Grid Engine (SGE) * Interoperability with other popular DTI tools: AFNI, Camino, FSL & DTIStudio * Interoperability with ITK-SNAP: support multi-modal visualization and segmentation

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• SciCrunch
• 14 years ago - by Anonymous

Implemented under MATLAB, this DTI image processing toolbox provides import-filters for several MR file standards, a processing unit to calculate the diffusion tensors; several GUI based tools to calculate fiber tracks and to evaluate the DTI dataset. The results can be filed as images with 3D impression or can be logged in formatted ASCII files. Tools and features: * DTI Processing Unit: Calculates the diffusion tensors and their eigenvalues and eigenvectors. Different file formats are supported (like DICOM, Bruker, binary files, Matlab structures). The standard SIEMENS and GE diffusion encoding schemes are supported; other schemes have to be defined in a separate text, .m or .mat file. * FiberTracking: ** Fiber tracking is realized by using the FACT algorithm (Mori et al., Annal. Neurol 1999). ** Probabilistic tracking realized by using the PiCo (Parker et al., JMRI 2003) approach but with DTI data as basis. It is possible to extract pathways between two seeds by combining two maps (Kreher et al., NeuroImage 2008). ** Global Fiber Tracking on basis of HARDI or DTI data. The method is based on the approach reported in (Marco Reisert et al: Global fiber reconstruction becomes practical. NeuroImage 54(2):955-62) * FiberViewer: ** Visualization and Navigation through different data modalities like DTI maps, fiber tracks, diffusion main directions. ** Supports different kinds of DTI maps (e.g. FA, Trace, lambda images ) ** Creation and manipulation of mask based ROIs. ** Selection of streamline fibers ** Visualization of probabilistic fiber tracking results ** Documentation by logging statistics of ROIs and fiber tracks into text files. ** Import/Export from/to ANALYZE or Nifti * 3D Visualizer: Visualization of map slices, ROIs, and fiber tracks with 3D impression. * Batch Editor: Automatic processing of high amounts of data. Possibility to link processing with SPM8 easily.

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• SciCrunch
• 14 years ago - by Anonymous

Recognizing the importance of research in Neuroscience and its great promise, as well as the importance of educating the neuroscientists of the future, the University of California, Davis, in 1990, established The Center for Neuroscience. The Center has now become the focus of interdisciplinary studies in Cellular, Molecular, Systems, Cognitive and Translational Neuroscience, with a Faculty made up of world leaders in brain research. The Center occupies facilities especially designed to promote and foster interactions among the resident faculty, associated faculty, postdoctoral fellows, and graduate students, with state-of-the-art lab space and associated facilities such as cellular and molecular imaging, functional imaging of the human brain and extensive databasing facilities. The Center provides an attractive setting for seminar series that feature distinguished National and International guest speakers as well as speakers from the UC Davis community of scientists. The Center is home to a number of visiting scholars each year and enjoys a lively intellectual atmosphere.

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• SciCrunch
• 17 years ago - by Anonymous

Crowdsourcing site for annotating neuroimaging literature. Brainspell also allows for search across the literature.

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• SciCrunch
• 14 years ago - by Anonymous

Free, open-source, object-oriented software package for analysis and reconstruction of Diffusion MRI data, tractography and connectivity mapping. The toolkit implements standard techniques, such as diffusion tensor fitting, mapping fractional anisotropy and mean diffusivity, deterministic and probabilistic tractography. It also contains more specialized and cutting-edge techniques, such as Monte-Carlo diffusion simulation, multi-fibre and HARDI reconstruction techniques, multi-fibre PICo, compartment models, and axon density and diameter estimation. Camino has a modular design to enable construction of processing pipelines that include modules from other software packages. The toolkit is primarily designed for unix platforms and structured to enable simple scripting of processing pipelines for batch processing. Most users use linux, MacOS or a unix emulator like cygwin running under windows. However, the core code is written in Java and thus is simple to call from other platforms and programming environments, such as matlab running under unix or windows.

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• SciCrunch
• 14 years ago - by Anonymous

Project to define a roadmap for diffusion MR imaging of traumatic brain imaging and design an infrastructure to implement the recommendations and tested to ensure feasibility, disseminate results, and facilitate deployment and adoption. The research roadmap and infrastructure development will concentrate on three areas: 1) standardization of diffusion imaging methodology, 2) trial design and patient selection for acute or chronic therapy, and 3) development of multi-center collaborations and repositories for evaluating whether advanced diffusion imaging does improve decision making and TBI patients' outcomes. # DTI MRI reproducability: One of the major areas of investigation in this project is to study the reproducibility of data acquisition and image analysis algorithms. Understanding reproducibility defines a base level of deviation from which scans can be analyzed with statistical significance. As part of this work they are also developing site qualification criteria with the intention of setting limits on the MR system minimal performance for acceptable use in TBI evaluation. # Infrastructure for image storage, analysis and visualization: There is a continuing need to refine and extend software methods for diffusion MRI data analysis and visualization. Not only to translate tools into clinical practice, but also to encourage continuation of the innovation and development of new tools and techniques. To deliver upon these goals they are designing and implementing a storage and computational infrastructure to provide access to shared datasets and intuitive interfaces for analysis and visualization through a variety of tools. A strong emphasis has been placed on providing secure data sharing and the ability to add community defined common data elements. The infrastructure is built upon a Software-as-a-Service model, in which tools are hosted and managed remotely allowing users access through well-defined interfaces. The final service will also facilitate composition or orchestration of workflows composed of different analysis and processing tasks (for example using LONI or XNAT pipelines) with the ultimate goal of providing automated no-click evaluations of diffusion MRI data. # Tool development: The final aspect of this project aims to facilitate and encourage tool development and contribution. By providing access to open datasets, they will create a platform on which tool developers can compare and improve and their tools. When tools are sufficiently mature they can be exposed in the infrastructure mentioned above and used by researchers and other developers.

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• SciCrunch
• 14 years ago - by Anonymous

Database of raw data from people who have shared their direct-to-customer (DTC) genetic results from 23andMe, deCODEme or FamilyTreeDNA. Logged-In users can search the database for users with specific phenotypes and mass-download all corresponding SNP-datasets. This allows you to get datasets like All genotyping files of openSNP-users that have Alzheimer and the corresponding control group. They are currently working on providing API-access. You can also use JSON to get access to openSNP-data and some other ways: If you want to automate the file-downloads for a given phenotype the RSS-feeds could help you. Inside the RSS-XML there are 2 flags you could use to automatically create correct genotype-groups: gives you the variation of this user at the phenotype you are looking at and gives you the download link. If you were genotyped by 23andMe, deCODEme or FamilyTreeDNA (contact them regarding others) you can upload the raw genotype data which you can download from your DTC test provider. The data will then be openly available for the world to see and download. They also parse these SNPs and annotate them. For annotation they include the manually curated SNPedia and find Open Access primary publications which appear in the journals of The Public Library of Science (PLoS), an Open Access publishing group. Additionally they screen Mendeley, a crowd-sourced repository of scientific publications. You can also publish some of your phenotypes so some day it might get possible to associate some SNPs with phenotypes. You can also share your knowledge about SNPs and phenotypes with other users and can socialize.

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• SciCrunch
• 14 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database / display tool of genome scans, with a web interface that lets the user view the data. It does not perform any analyses - these must be done by other software, and the results uploaded into it. The basic features of GSCANDB are: * Parallel viewing of scans for multiple phenotypes. * Parallel analyses of the same scan data. * Genome-wide views of genome scans * Chromosomal region views, with zooming * Gene and SNP Annotation is shown at high zoom levels * Haplotype block structure viewing * The positions of known Trait Loci can be overlayed and queried. * Links to Ensembl, MGI, NCBI, UCSC and other genome data browsers. In GSCANDB, a genome scan has a wide definition, including not only the usual statistical genetic measures of association between genetic variation at a series of loci and variation in a phenotype, but any quantitative measure that varies along the genome. This includes for example competitive genome hybridization data and some kinds of gene expression measurements.

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• SciCrunch
• 14 years ago - by Anonymous

Collection of isogenic human cell lines that are deficient for the expression of single genes. The current collection is based on the human cell line KBM-7 (Kotecki et al. Experimental Cell Research 1999), which is haploid for all chromosomes except chromosome 8 and a small part of chromosome 15. In these cells, genes are disrupted by the means of a retroviral gene trap. The collection is being expanded to cover the majority of expressed genes. The Human Gene Trap Mutant Collection is generated as a public-private partnership between CeMM (the Research Center for Molecular Medicine of the Austrian Academy of Sciences) and Haplogen.

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• SciCrunch
• 14 years ago - by Anonymous

Portal for NIH, NIMH, and NINDS scientific and computer resources including Mac sites, PC sites, Linux sites, intramural programs, intranet and the NIH JumpStart and Directory.

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• SciCrunch
• 13 years ago - by Anonymous

Database contating hydrothermal spring geochemistry that hosts and serves the full range of compositional data acquired on seafloor hydrothermal vents from all tectonic settings. It can accommodate published historical data as well as legacy and new data that investigators contribute.

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• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Representational State Transfer (REST) model based service for accessing a set of Neuroscience Information Framework (NIF) data through a fixed set of operations. They are defined by a WADL file which allows clients to automatically generate code for these services. The services (AnnotateService, FederationService, LdaService, LexicalService, LiteratureService, QueryService, SummaryService, VocabularyService) include the ability to: * Retrieve a federation summary, e.g., http://nif-services.neuinfo.org/servicesv1/v1/summary?q=* * Retrieve data records from a NIF federation source for a search, e.g., http://nif-services.neuinfo.org/servicesv1/v1/federation/data/nif-0000-00007-1?q=purkinje * Retrieve registry data records from NIF, e.g., http://nif-services.neuinfo.org/servicesv1/v1/federation/data/nlx_144509-1?q=miame * Retrieve a complete search summary, e.g., http://nif-services.neuinfo.org/servicesv1/v1/federation/search?q=cortex * Retrieve NIF auto-complete suggestions, e.g., http://nif-services.neuinfo.org/servicesv1/v1/vocabulary?prefix=hippo * Use the NIF annotator for arbitrary text, e.g., http://nif-services.neuinfo.org/servicesv1/v1/annotate?content=The%20cerebellum%20is%20a%20wonderful%20thing These services are documented for developers in the WADL file (and client stubs should have the comments embedded in them). Visit, http://nif-services.neuinfo.org/servicesv1/ for more information

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• SciCrunch
• 14 years ago - by Anonymous

Public database that stores areas of genome that differ between individual genomes (variants) and, where available, associated disease and phenotype information. Different types of variants for several species: single nucleotide polymorphisms (SNPs), short nucleotide insertions and/or deletions, and longer variants classified as structural variants (including CNVs). Effects of variants on the Ensembl transcripts and regulatory features for each species are predicted. You can run same analysis on your own data using Variant Effect Predictor. These data are integrated with other data sources in Ensembl, and can be accessed using the API or website. For several different species in Ensembl, they import variation data (SNPs, CNVs, allele frequencies, genotypes, etc) from a variety of sources (e.g. dbSNP). Imported variants and alleles are subjected to quality control process to flag suspect data. In human, they calculate linkage disequilibrium for each variant, by population.

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• SciCrunch
• 14 years ago - by Anonymous

Database of human SNPs in predicted miRNA-mRNA binding sites, based on information from dbSNP135 and mirBASE18. MirSNP is highly sensitive and covers most experiments confirmed SNPs that affect miRNA function. MirSNP may be combined with researchers' own GWAS or eQTL positive data sets to identify the putative miRNA-related SNPs from traits/diseases associated variants. They aim to update the MirSNP database as new versions of mirBASE and dbSNP database become available.

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• SciCrunch
• 14 years ago - by Anonymous