Tools   Select Another Resource Report Type

http://mialab.mrn.org/index.html

MIALAB, headed by Dr. Vince Calhoun, focuses on developing and optimizing methods and software for quantitative analysis of structure and function in medical images with particular focus on the study of psychiatric illness. We work with many types of data, including functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), electroencephalography (EEG), structural imaging and genetic data. Much of our time is spent working on new methods for flexible analysis of brain imaging data. The use of data driven approaches is very useful for extracting potentially unpredictable patterns within these data. However such methods can be further improved by incorporating additional prior information as constraints, in order to benefit from what we know. To this end, we draw heavily from the areas of image processing, adaptive signal processing, estimation theory, neural networks, statistical signal processing, and pattern recognition.

Proper citation: MIALAB - Medical Image Analysis Lab (RRID:SCR_006089) Copy   

•   Source: SciCrunch Registry

https://dsigdb.tanlab.org/DSigDBv1.0/

Online database provides collection of gene sets based on quantitative inhibition and/or drug-induced gene expression changes data of drugs and compounds. Allows users to search, view and download drugs/compounds and gene sets.

Proper citation: DSigDB (RRID:SCR_026202) Copy   

•   Source: SciCrunch Registry

http://www.ncibi.org/

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   

•   Source: SciCrunch Registry

https://camera.niehs.nih.gov/

Interactive database and user interface providing online access to validated alternative methods for U.S. regulatory and other contexts of use. Central hub and unified resource of validated alternative methods that enhances accessibility to validation study reports, data, protocols / SOPs, and information on regulatory guidance.Users can filter searches by alternative method types, defined approaches, Test Method Endpoint, and regulatory guidance.

Proper citation: Collection of Alternative Methods for Regulatory Application (CAMERA) (RRID:SCR_027893) Copy   

•   Source: SciCrunch Registry

https://github.com/ABCD-STUDY/eprime-data-clean

Software to convert E-Prime (software tool for psychology computerized experiment design, data collection, and analysis) generated files to CSV files without errors during conversion. The ABCD project is using E-Prime to run behavioral tests.

Proper citation: eprime-data-clean (RRID:SCR_016020) Copy   

•   Source: SciCrunch Registry

http://www.cytobank.org/index.html

A cloud-based platform which allows users to analyze, visualize, and archive multiparamter cytometry data for single-cell biology. Multiple single-cell data sets can be analyzed and visualized simultaneously with a variety of graphics, inlcuding Sunburst, SPADE, and viSNE. Users can store and back up related data such as protocols, microscopy images, and presentations and collaborate and share analysis and data sets with other Cytobank users. Cytobank also provides a variety of services and training sessions to assist with experiment workflow.

Proper citation: Cytobank (RRID:SCR_014043) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000363.v16.p10

Project to generate extensive biomarker data from Framingham Heart Study participants using immunoassays, proteomics, metabolomics/lipomics, and gene expression and microRNA profiling to advance personalized medicine through biomarker discovery and validation.

Proper citation: SABRe CVD Initiative (RRID:SCR_016572) Copy   

•   Source: SciCrunch Registry

https://sleepdata.org/datasets/ccshs

Portal for population based pediatric cohorts studied with objective sleep studies. Includes children with in-home sleep studies, acoustic reflectometry, anthropometry, spirometry, blood pressure (BP), and neuropsychology (NP) and behavioral assessments. Signals recorded include EEG, ECG, EOG, EMG, SpO2, airflow (thermocouple) nasal pressure, respiratory effort, position, plethysmography, light, HR.

Proper citation: Cleveland Children's Sleep and Health Study (RRID:SCR_016584) Copy   

•   Source: SciCrunch Registry

https://sleepdata.org/datasets/bestair/

Portal for sleep study to address challenges in conducting future large-scale trials of sleep apnea treatment. Includes data from sleep apnea patients with cardiovascular disease or risk factors. Signals included in the polysomnography (PSG) montage are ECG, SpO2, airflow, nasal pressure, position, pulse, respiratory effort, snore, tidal volume.

Proper citation: Best Apnea Interventions for Research (BestAIR) sleep study (RRID:SCR_016583) Copy   

•   Source: SciCrunch Registry

https://neurobot.incf.org

Software tool for data management in clinical studies to improve care for patients with Traumatic Brain Injury (TBI). Used to search and find study variables with the associated information and export study data for further analysis.

Proper citation: INCF-Neurobot (RRID:SCR_017004) Copy   

•   Source: SciCrunch Registry

https://www.daqcord.org/

Software tool for practical self assessment and reporting method for clinical research studies, to capture key information about data acquisition and quality control measures. Linked to dataset so that potential research collaborators can determine if data meets their needs and expectations.

Proper citation: DAQCORD (RRID:SCR_017395) Copy   

•   Source: SciCrunch Registry

https://usdrn.org/

Portal for research on urinary stones in adults and children in order to learn more about who forms kidney stones, treatments and prevention. Network comprises of experts including adult and pediatric urologists, adult and pediatric nephrologists, pediatricians, emergency department physicians, clinical trialists, nutritionists, behavioral scientists, and radiologists. Duke Clinical Research Institute is Scientific Data Research Center and with clinical sites including University of Pennsylvania Children Hospital of Philadelfia, University of Texas Southwestern Medical Center, University of Washington, Washington University in St. Louis, work together in planning, executing, and analyzing results from USDRN studies.

Proper citation: Urinary Stone Disease Research Network (RRID:SCR_019059) Copy   

•   Source: SciCrunch Registry

http://www.chemspider.com/

Collection of chemical structures. Provides access to structures, properties and associated information from hundreds of data sources to find compounds of interest and provides services to improve this data by curation and annotation and to integrate it with users applications.

Proper citation: ChemSpider (RRID:SCR_006360) Copy   

•   Source: SciCrunch Registry

https://repository.niddk.nih.gov/home/

NIDDK Central Repositories are two separate contract funded components that work together to store data and samples from significant, NIDDK funded studies. First component is Biorepository that gathers, stores, and distributes biological samples from studies. Biorepository works with investigators in new and ongoing studies as realtime storage facility for archival samples.Second component is Data Repository that gathers, stores and distributes incremental or finished datasets from NIDDK funded studies Data Repository helps active data coordinating centers prepare databases and incremental datasets for archiving and for carrying out restricted queries of stored databases. Data Repository serves as Data Coordinating Center and website manager for NIDDK Central Repositories website.

Proper citation: NIDDK Central Repository (RRID:SCR_006542) Copy   

•   Source: SciCrunch Registry

https://fitbir.nih.gov/

Platform for Traumatic Brain Injury relevant data. System was developed to share data across entire TBI research field and to facilitate collaboration between laboratories and interconnectivity between informatics platforms. FITBIR implements interagency Common Data Elements for TBI research and provides tools and resources to extend data dictionary. Established submission strategy to ensure high quality and to provide maximum benefit to investigators. Qualified researchers can request access to data stored in FITBIR and/or data stored at federated repositories.

Proper citation: Federal Interagency Traumatic Brain Injury Research Informatics System (RRID:SCR_006856) Copy   

•   Source: SciCrunch Registry

http://www.ars-grin.gov/

Web server to provide germplasm information about plants, animals, microbes, invertebrates and access to databases that maintain passport, characterization, evaluation, inventory, and distribution data for the management and utilization of national germplasm collections. Under control of the U.S. Department of Agriculture's Agricultural Research Service to support the National Genetic Resources Program (NGRP). Operated by the Database Management Unit of the National Germplasm Resource Laboratory in Beltsville, Maryland.

Proper citation: Germplasm Resources Information Network (RRID:SCR_006675) 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

http://human.brain-map.org/static/brainexplorer

Multi modal atlas of human brain that integrates anatomic and genomic information, coupled with suite of visualization and mining tools to create open public resource for brain researchers and other scientists. Data include magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), histology and gene expression data derived from both microarray and in situ hybridization (ISH) approaches. Brain Explorer 2 is desktop software application for viewing human brain anatomy and gene expression data in 3D.

Proper citation: Allen Human Brain Atlas (RRID:SCR_007416) Copy   

•   Source: SciCrunch Registry

https://bams1.org/

Knowledge management system designed to handle neurobiological information at different levels of organization of vertebrate nervous system. Database and repository for information about neural circuitry, storing and analyzing data concerned with nomenclature, taxonomy, axonal connections, and neuronal cell types. Handles data and metadata collated from original literature, or inserted by scientists that is associated to four levels of organization of vertebrate nervous system. Data about expressed molecules, neuron types and classes, brain regions, and networks of brain regions.

Proper citation: Brain Architecture Management System (RRID:SCR_007251) Copy   

•   Source: SciCrunch Registry

http://wwwmgs.bionet.nsc.ru/mgs/gnw/about.shtml

GeneNetWorks is designed for accumulation of experimental data, data navigation, data analysis, and analysis of dependencies in the field of gene expression regulation. It integrates the databases and programs for processing the data about structure and function of DNA, RNA, and proteins, together with the other information resources important for gene expression description. The unique property of above described system is that all the resources within the system GeneNetWorks are divided according to the natural hierarchy of molecular genetic systems and has the following levels: (1) DNA; (2) RNA; (3) proteins; and (4) gene networks. Each module contains: 1) experimental data represented as a database or some sample; 2) program for data analysis; 3) results of an automated data processing; 4) tools for the graphical representation of these data and the results of the data analyses.

Proper citation: GeneNetWorks (RRID:SCR_008034) Copy   

•   Source: SciCrunch Registry