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A large multi-site pediatric MRI and genetics data resource to facilitate studies of the genomic landscape of the developing human brain. It includes information about the developing mental and emotional functions of the children to understand the genetic basis of individual differences in brain structure and connectivity, cognition, and personality. Investigators on the project are studying 1400 children between the ages of 3 and 20 years so that links between genetic variation and developing patterns of brain connectivity can be examined. Investigators interested in the effects of a particular gene will be able to search the database for any brain areas or connections between areas that differ as a function of variation in a particular gene, and also to determine if the genes appear to affect the course of brain development at some point during childhood. A data exploration tool has been created for mapping and analyzing MRI data sets collected for PING and related developmental studies. Approved investigators will be able to view raw image sets and derived 3D brain maps of MRI and DTI data, conduct hypothesis testing, and graph brain area measures as they change across the time course of development. PING Cores * Coordinating Core: Functions include project management, screening of participants and maintaining the database * Neuroimaging Core: applying a standardized high-resolution structural MRI protocol involving 3-D T1-weighted scans, a T2-weighted volume, and a set of diffusion-weighted scans with multiple b values and diffusion directions, scans to estimate MRI relaxation rates, and gradient echo EPI scans for resting state fMRI. Importantly, adaptive motion compensation, using ����??PROMO����??, a novel real-time motion correction algorithm will be used. Specific PING protocols for each scanner manufacturer: ** PING MRI Protocol - GE ** PING MRI Protocol - Philips ** PING MRI Protocol - Siemens * Assessment Core: Cognitive assessments for the PING project are conducted using the NIH Toolbox for Cognition. * Genomics Core: functions as a central repository for receipt of saliva samples collected for each study participant. Once received, samples are catalogued, maintained, and DNA is extracted using state-of-the-field laboratory techniques. Ultimately, genome-wide genotyping is performed on the extracted DNA using the Illumina Human660W-Quad BeadChip. PING involves 10 sites throughout the country including UCSD, University of Hawaii, Scripps Genomics, UCLA, UC Davis, Kennedy Krieger Institute/Johns Hopkins, Sacker Institute/Cornell University, University of Massachusetts, Massachusetts General Hospital/Harvard, and Yale. Families who may want to participate in the study, or others who want to know more about it, may email questions to ping (at) ucsd.edu.
Proper citation: Pediatric Imaging Neurocognition and Genetics (RRID:SCR_008953) Copy
http://www.incf.org/resources/data-space/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 21, 2017.
Repository for sharing of neuroscience data, text, images, sounds, movies, models and simulations.
Proper citation: INCF Dataspace (RRID:SCR_000158) Copy
Central online repository for microRNA nomenclature, sequence data, annotation and target prediction.Collection of published miRNA sequences and annotation.
Proper citation: miRBase (RRID:SCR_003152) Copy
Repository to host data and tools associated with articles published by GigaScience & GigaByte journals. GigaDB defines a dataset as a group of files (e.g., sequencing data, analyses, imaging files, software programs) that are related to and support an article or study. Through their association with DataCite, each dataset will be assigned a DOI that can be used as a standard citation for future use of these data in other articles by the authors and other researchers. Datasets in GigaDB all require a title that is specific to the dataset, an author list, and an abstract that provides information specific to the data included within the dataset. Detailed information about the dataset is curated by dedicated biocurators in collaboration with the article authors at the time of publication of the associated manuscript to ensure full transparency and reproducibility of all journal articles published in GigaScience and GigaByte journals.
Proper citation: GigaDB (RRID:SCR_004002) Copy
http://www.liberatingresearch.org
A repository which hosts and archives original and edited scientific papers. Scientists can post their academic manuscripts on Libre, where they can find reviewers who will formally evaluate the manuscripts. Evaluated works are posted alongside the original manuscript with reviewers' identities disclosed and the work they edit given its own DOI. Users can post additional updated versions of their work to Libre or send their papers to journals. Papers and reviews are rated by other scientists, and from these Libre creates holistic indeces listing the best rated writers and reviewers.
Proper citation: Libre (RRID:SCR_014018) Copy
http://grouthbio.com/Home_Page.html
A comprehensive listing of companies and organizations involved with genomics and molecular biology. There are lists for genome software and services, genome institutions and supplies, and general institutions.
Proper citation: Geoffs Bio-Directories (RRID:SCR_001016) Copy
Open-source web application for managing digital repositories. Allows to create custom computing environments that can be shared and used by many remote users.Turns a GitHub repository containing a collection of Jupyter Notebooks into a collection of interactive notebooks. With Binder, open those notebooks in an executable environment, making your code immediately reproducible by anyone, anywhere.
Proper citation: Binder (RRID:SCR_016437) Copy
Repository of sequenced antibodies, integrating curated information about antibody and its antigen with cross links to standardized databases of chemical and protein entities. Manually curated repository of sequenced antibodies, developed by Geneva Antibody Facility at University of Geneva, in collaboration with CALIPHO and Swiss Prot groups at SIB Swiss Institute of Bioinformatics. Database provides list of sequenced antibodies with their known targets. Each antibody is assigned unique ID number that can be used in academic publications to increase reproducibility of experiments.
Proper citation: ExPASy ABCD database (RRID:SCR_017401) Copy
http://www.epilepsygenes.org/page/show/homepage
The Epilepsy Genetic Association Database (epiGAD) is an online repository of data relating to genetic association studies in the field of epilepsy. It summarizes the results of both published and unpublished studies, and is intended as a tool for researchers in the field to keep abreast of recent studies, providing a bird''s eye view of this research area. The goal of epiGAD is to collate all association studies in epilepsy in order to help researchers in this area identify all the available gene-disease associations. Finally, by including unpublished studies, it hopes to reduce the problem of publication bias and provide more accurate data for future meta-analyses. It is also hoped that epiGAD will foster collaboration between the different epilepsy genetics groups around the world, and faciliate formation of a network of investigators in epilepsy genetics. There are 4 databases within epiGAD: - the susceptibility genes database - the epilepsy pharmacogenetics database - the meta-analysis database - the genome-wide association studies (GWAS) database The susceptibility genes database compiles all studies related to putative epilepsy susceptibility genes (eg. interleukin-1-beta in TLE), while the pharmacogenetics studies in epilepsy (eg. ABCB1 studies) are stored in ''phamacogenetics''. The meta-analysis database compiles all existing published epilepsy genetic meta-analyses, whether for susceptibility genes, or pharmacogenetics. The GWAS database is currently empty, but will be filled once GWAS are published. Sponsors: The epiGAD website is supported by the ILAE Genetics Commission.
Proper citation: Epilepsy Genetic Association Database (RRID:SCR_006840) Copy
https://github.com/srkesler/bnets
Software repository containing code for measuring brain networks from structural and functional MRI data. Several programs require MATLAB to run.
Proper citation: Brain Networks Toolbox (RRID:SCR_014788) Copy
A data repository containing transcriptome and associated metadata for the developing and adult human brain. It provides genome-wide, exon-level transcriptome data from both sexes and multiple ethnicities.
Proper citation: Human Brain Transcriptome (RRID:SCR_013742) Copy
Service that exports your Git repository to the new W3C PROV standard. Your Git repositories are a goldmine of provenance information, tracking the evolution of your code or data and the activities of the people involved. This information could be linked to other similar provenance data by exporting it in the provenance interchange W3C recommendation PROV (http://www.w3.org/TR/prov-overview/).
Proper citation: Git2PROV (RRID:SCR_002625) Copy
https://github.com/ClawBio/ClawBio
Software AI agent skill library designed to run automated biological and genomic data analyses. Provides curated repository of pre-built, expert validated scientific pipelines that AI agents can look up and execute perfectly every time.
Proper citation: ClawBio (RRID:SCR_029026) Copy
The Center develops conceptual models, computational infrastructure, an integrated knowledge repository, and query and analysis tools that enable scientists to effectively access and integrate the wealth of biological data. The National Center for Integrative Biomedical Informatics (NCIBI) was founded in October 2005 and is one of seven National Centers for Biomedical Computing (NCBC) in the NIH Roadmap. NCIBI is based at the University of Michigan as a part of the Center for Computational Medicine and Biology (CCMB). NCIBI is composed of biomedical researchers, computational biologists, computer scientists, developers and human-computer interaction specialists organized into seven major core functions. They work in interdisciplinary teams to collectively develop tools that are not only computationally powerful but also biologically relevant and meaningful. The four initial Driving Biological Projects (prostate cancer progression, Type 1 and type 2 diabetes and bipolar disorder) provide the nucleation point from which tool development is informed, launched, and tested. In addition to testing tools for function, a separate team is dedicated to testing usability and user interaction that is a unique feature of this Center. Once tools are developed and validated the goal of the Center is to share and disseminate data and software throughout the research community both internally and externally. This is achieved through various mechanisms such as training videos, tutorials, and demonstrations and presentations at national and international scientific conferences. NCIBI is supported by NIH Grant # U54-DA021519.
Proper citation: National Center for Integrative Biomedical Informatics (RRID:SCR_001538) Copy
https://www.creates-nmaist.ac.tz/
Serves as a regional hub for developing sustainable agricultural solutions, bio-nanoscience, and climate resilience technologies in East and Southern Africa.Includes bio-repository for research and data repository to predict risks from climate variability. Works with partners such as the UNESCO National Commission in Tanzania and Ifakara Health Institute (IHI) to support malaria medicine discovery and regional nano-hubs.
Proper citation: Nelson Mandela African Institution of Science and Technology Africa Centre for Research, Agricultural Advancement, Teaching Excellence and Sustainability Core Facility (RRID:SCR_028120) Copy
https://github.com/JenHungWang/ECTI_Atopic_Dermatitis/blob/master/README.md
Software repository presents objective, quantifiable method for assessing severity of atopic dermatitis.
Proper citation: ECTI_Atopic_Dermatitis (RRID:SCR_025706) Copy
https://github.com/enveda/chemical-space-estimation/
Software repository contains scripts and notebooks for defining the limits, challenges and estimations of plant chemical space using MS data.
Proper citation: Chemical space estimation of plants (RRID:SCR_026498) Copy
Open ecosystem of data repositories hosted by various partner organizations, who work together to ensure that their data can be federated across participating platforms. Open source platform for biomedical researchers to access data, run analysis tools, and collaborate. Terra powers important scientific projects including AnVIL, BioData Catalyst, Human Cell Atlas, BICCN, and many others. Easily access both open and access-controlled datasets hosted in cloud repositories. Explore, analyze, and visualize data using Jupyter Notebooks, RStudio, RShinyApps, and Galaxy.
Proper citation: Terra (RRID:SCR_021648) Copy
http://openconnectomeproject.org/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. Connectomes repository to facilitate the analysis of connectome data by providing a unified front for connectomics research. With a focus on Electron Microscopy (EM) data and various forms of Magnetic Resonance (MR) data, the project aims to make state-of-the-art neuroscience open to anybody with computer access, regardless of knowledge, training, background, etc. Open science means open to view, play, analyze, contribute, anything. Access to high resolution neuroanatomical images that can be used to explore connectomes and programmatic access to this data for human and machine annotation are provided, with a long-term goal of reconstructing the neural circuits comprising an entire brain. This project aims to bring the most state-of-the-art scientific data in the world to the hands of anybody with internet access, so collectively, we can begin to unravel connectomes. Services: * Data Hosting - Their Bruster (brain-cluster) is large enough to store nearly any modern connectome data set. Contact them to make your data available to others for any purpose, including gaining access to state-of-the-art analysis and machine vision pipelines. * Web Viewing - Collaborative Annotation Toolkit for Massive Amounts of Image Data (CATMAID) is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by Google Maps, enhanced to allow the exploration of 3D image data. View the fork of the code or go directly to view the data. * Volume Cutout Service - RESTful API that enables you to select any arbitrary volume of the 3d database (3ddb), and receive a link to download an HDF5 file (for matlab, C, C++, or C#) or a NumPy pickle (for python). Use some other programming language? Just let them know. * Annotation Database - Spatially co-registered volumetric annotations are compactly stored for efficient queries such as: find all synapses, or which neurons synapse onto this one. Create your own annotations or browse others. *Sample Downloads - In addition to being able to select arbitrary downloads from the datasets, they have also collected a few choice volumes of interest. * Volume Viewer - A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels. The code and program can be downloaded. * Machine Vision Pipeline - They are building a machine vision pipeline that pulls volumes from the 3ddb and outputs neural circuits. - a work in progress. As soon as we have a stable version, it will be released. * Mr. Cap - The Magnetic Resonance Connectome Automated Pipeline (Mr. Cap) is built on JIST/MIPAV for high-throughput estimation of connectomes from diffusion and structural imaging data. * Graph Invariant Computation - Upload your graphs or streamlines, and download some invariants. * iPad App - WholeSlide is an iPad app that accesses utilizes our open data and API to serve images on the go.
Proper citation: Open Connectome Project (RRID:SCR_004232) Copy
Data repository where researchers can publicly store and share unthresholded statistical brain activation maps produced by MRI and PET studies.
Proper citation: NeuroVault (RRID:SCR_003806) Copy
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