Tools   Select Another Resource Report Type

https://sparc.science

The SPARC data repository as of 2023 is an open data repository developed as part of the NIH SPARC initiative and has been used by SPARC funded investigator groups to curate and publish high quality datasets related to the autonomic nervous system. We are thrilled that as of August 2022, SPARC is accepting datasets from investigators that are not funded through the NIH SPARC program. The NIH's Common Fund Stimulating Peripheral Activity to Relieve Conditions (SPARC) program aims to transform our understanding of these nerve-organ interactions and ultimately advance neuromodulation field toward precise treatment of diseases and conditions for which conventional therapies fall short.

Proper citation: SPARC Project (RRID:SCR_017041) Copy   

•   Source: SciCrunch Registry

https://alleninstitute.org/

Non profit bioscience research organization in Seattle, Washington dedicated to accelerating research globally and sharing that data within the science community. Allen Institute for Brain Science, Allen Institute for Cell Science, Allen Institute for Immunology, and The Paul G. Allen Frontiers Group are four divisions of this Institute with commitment to open science model within its research institutes.

Proper citation: Allen Institute (RRID:SCR_005435) Copy   

•   Source: SciCrunch Registry

http://neuroinformatics.usc.edu/

The USC Brain Project is engaged in the effort to develop new tools and methodologies for neuroinformatics in modeling neural mechanisms of visuomotor coordination and exploring the evolution of the human language-ready brain, as well as conducting work in both neural modeling and database construction in relation to rehabilitation after stroke. Sponsors: USCBP is funded by the University of Southern California.

Proper citation: University of Southern California Brain Project (RRID:SCR_008044) Copy   

•   Source: SciCrunch Registry

https://www.humanconnectome.org/software/connectome-workbench

Software brain visualization, analysis and discovery tool for fMRI and dMRI brain imaging data, including functional and structural connectivity data generated by the Human Connectome Project. Used to map brain imaging data. Allows for visualization of outputs from HCP pipelines from single subject, or average data from group of subjects and register that data onto standard brain atlas.

Proper citation: Connectome Workbench (RRID:SCR_008750) Copy   

•   Source: SciCrunch Registry

http://www.biobankcentral.org/resource/wwibb.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on March 27, 2013. Web-based portal to connect all the constituencies in the global biobank community. The project seeks to increase the transparency and accessibility of the scientific research process by connecting researchers with an additional source of funding - microinvestments received from the broader online community. In exchange for these public investments, researchers will maintain research logs detailing the play-by-play progress made in their project, as well as publishing all of their data in a public database under a science commons license. These research projects, in turn, will serve to continually update a research-based neuroscience-based human brain & body curriculum. Biobanks are the meeting point of two major information trends in biomedical research: the generation of huge amounts of genomic and other laboratory data, and the electronic capture and integration of patient clinical records. They are comprised of large numbers of human biospecimens supplemented with clinical data. Biobanks when implemented effectively can harness the power of both genomic and clinical data and serve as a critical bridge between basic and applied research, linking laboratory to patient and getting to cures faster. As science and technology leaders work to address the many challenges facing U.S. biobanks logistical, technical, ethical, financial, intellectual property, and IT BioBank Central will serve as an accurate and timely source of knowledge and news about biorepositories and their role in research and drug development. The Web site also provides a working group venue, patient and public education programs, and a forum for international collaboration and harmonization of best practices.

Proper citation: BioBank Central (RRID:SCR_008645) Copy   

•   Source: SciCrunch Registry

https://www.sciencescott.com/pyminer

Software tool to automate cell type identification, cell type-specific pathway analyses, graph theory-based analysis of gene regulation, and detection of autocrine-paracrine signaling networks. Finds Gene and Autocrine-Paracrine Networks from Human Islet scRNA-Seq.

Proper citation: PyMINEr (RRID:SCR_016990) Copy   

•   Source: SciCrunch Registry

http://clendening.kumc.edu/dc/rti/

Database of images from medical and natural history texts, most of which were printed before 1800. They are organized by theme: diagnostics, human body, imaging, instruments, physician-patient culture, portraits, public health, reproduction, reproduction instruments, therapeutics. The Clendening History of Medicine Library and Museum is the rare books and manuscripts library of the University of Kansas Medical Center. We actively collect rare books as well as current works in the history of medicine, nursing, and the allied professions. The Library also supports the biomedical ethics and medical humanities curriculum by collecting contemporary secondary works in these areas. Under the auspices of its Museum, the Library also owns hundreds of medical artifacts.

Proper citation: Images from the Clendening Library (RRID:SCR_002379) Copy   

•   Source: SciCrunch Registry

http://sagebase.org/

Non-profit biomedical research organization developing predictors of disease and accelerating health research through creation of open systems, incentives, and standards. Formed to coordinate and link academic and commercial biomedical researchers through Commons that represents new paradigm for genomics intellectual property, researcher cooperation, and contributor evolved resources.

Proper citation: Sage Bionetworks (RRID:SCR_003384) Copy   

•   Source: SciCrunch Registry

http://camrd4.mc.duke.edu/

Research facility of the Department of Radiology at the Duke University Medical Center (DUMC) providing access to a whole-body, commercially manufactured 3 Tesla (Trio, Siemens Medical Systems) MR Imaging and Spectroscopy System with full research capability. The Center is fully equipped to perform clinical and research MR imaging or spectroscopy studies on humans or large animals. A full range of monitoring, anesthesia, RF coil development, computer and instrumental control facilities as well as MR research technologists and physics/chemistry consultation are available to Department of Radiology researchers and their collaborators.

Proper citation: CAMRD (RRID:SCR_001713) Copy   

•   Source: SciCrunch Registry

http://phenotype.mc.vanderbilt.edu/

Collaborative environment of building and validating electronic phenotype algorithms using electronic medical records (EMRs) and natural language processing (NLP) for use in genome-wide association studies (GWAS). On this site you can: View existing algorithms, Enter or create new algorithms, Collaborate with others to create or review algorithms, View implementation details for existing algorithms. The Electronic Medical Records and Genomics Network (eMERGE) has investigated whether data captured through routine clinical care using electronic medical records (EMRs) can identify disease phenotypes with sufficient positive and negative predictive values for use in genome-wide association studies (GWAS). Most EMRs captured key information (diagnoses, medications, laboratory tests) used to define phenotypes in a structured format; in addition, natural language processing has also been shown to improve case identification rates. PheKB is an outgrowth of that validation effort. Phenotype algorithms can be viewed by data modalities or methods used: CPT codes, ICD 10 codes, ICD 9 codes, Laboratories, Medications, Vital Signs, Natural Language Processing Algorithms can also be viewed by: * Implementation results (positive predictive value, sensitivity, publications) * Institution * Work Group

Proper citation: PheKB (RRID:SCR_005292) Copy   

•   Source: SciCrunch Registry

http://www.simulations-plus.com/Products.aspx?pID=13

Software program for advanced predictive modeling of Absorption, Distribution, Metabolism, Elimination, and Toxicity (ADMET) properties of chemical substances in the human body. ADMET Predictor can estimate a number of vital ADMET properties (listed below) from molecular structures and build predictive models of new properties from user's data.

Proper citation: ADMET Predictor (RRID:SCR_014903) Copy   

•   Source: SciCrunch Registry

http://genomics.senescence.info/

Collection of databases and tools designed to help researchers study the genetics of human ageing using modern approaches such as functional genomics, network analyses, systems biology and evolutionary analyses. A major resource in HAGR is GenAge, which includes a curated database of genes related to human aging and a database of ageing- and longevity-associated genes in model organisms. Another major database in HAGR is AnAge. Featuring over 4,000 species, AnAge provides a compilation of data on aging, longevity, and life history that is ideal for the comparative biology of aging. GenDR is a database of genes associated with dietary restriction based on genetic manipulation experiments and gene expression profiling. Other projects include evolutionary studies, genome sequencing, cancer genomics, and gene expression analyses. The latter allowed them to identify a set of genes commonly altered during mammalian aging which represents a conserved molecular signature of aging. Software, namely in the form of scripts for Perl and SPSS, is made available for users to perform a variety of bioinformatic analyses potentially relevant for studying aging. The Perl toolkit, entitled the Ageing Research Computational Tools (ARCT), provides modules for parsing files, data-mining, searching and downloading data from the Internet, etc. Also available is an SPSS script that can be used to determine the demographic rate of aging for a given population. An extensive list of links regarding computational biology, genomics, gerontology, and comparative biology is also available.

Proper citation: Human Ageing Genomic Resources (RRID:SCR_007700) Copy   

•   Source: SciCrunch Registry

http://archive.cnbc.cmu.edu/Resources/disordermodels/index.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. This site aims to provide a discussion and source list for connectionist and neural network models of disorders associated with mental or brain conditions. Recent connectionist and neural network models of behavior, information processing patterns, and brain activity present in people with cognitive, affective, brain, and behavioral disorders are reviewed on this web site. Ways that assumptions regarding normal and disordered behavior may be represented in connectionist models are discussed for features of various disorders. Similarities and differences between the models and criteria for their evaluation are presented, and suggestions for inclusion of information which may help to make these models more directly comparable in the future are considered. References to Connectionist Models of Cognitive, Affective, Brain, and Behavioral Disorders include: General Neural Network Information Reviews, General Introductions, and Calls for More Connectionist Models of Mental Disorders Models of Psychopathologies and Psychiatric Disorders Models of Cognitive, Affective, Brain, and Behavioral Disorders Not Associated with Psychopathology Additionally, Web Sites for Neural Network Modelers of Disorder are provided.

Proper citation: Connectionist Models of Cognitive, Affective, Brain, and Behavioral Disorders (RRID:SCR_008088) Copy   

•   Source: SciCrunch Registry

http://www.cnbc.cmu.edu/ibsc/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 07, 2013. A framework for understanding human cognition, grounded in principles specifying the character of human cognitive processes, and constrained by properties, of the underlying neural mechanisms. The Center will exploit this framework to guide formulation of explicit, testable models of normal and disordered cognition, including models of the development of cognitive functions and of their disintegration as a result of brain damage or disease. This site is intended as a public service and as a focal point for exchange of ideas among the participants in the Interdisciplinary Behavioral Science Center (IBSC). Public areas of the site provide information about the Center as a whole and about the various projects in the Center, as well as web-accessible documents and tools that we are making available as a public service. A fundamental tenet is that cognition is an emergent phenomenon, arising from the interactions of cooperating processing elements organized into specialized populations. One aim of the center will be to investigate the utility of explicit models that are formulated in terms of this approach, addressing many aspects of cognition including semantic knowledge, language processing, cognitive control, perception, learning and memory. A second aim will also investigate the principles that are embodied in the models, including principles of learning, processing and representation. Learning will be a central focus, since it plays a crucial role in cognitive development, acquisition of skills, formation of memories, and remediation of cognitive functions. A third aim of the Center will be to incorporate constraints from neuroscience. Findings from neuroscience will guide the specification of the principles and the formulation of domain-specific details of particular models, and will provide target experimental observations against which to assess the adequacy of the models. In addition, the Center will make use of neurophysiological methods in animals and functional brain imaging in humans to test predictions and generate additional data needed to constrain and inform model development. The Center will provide training funds for interdisciplinary research fellowships, to train junior scientists in the convergent use of behavioral, computational, and neuroscience methodologies. The outcome of the Centers efforts will be a fuller characterization of the nature of human cognitive processes, a clearer formulation of the underlying principles, and a more complete understanding of normal and disordered functions across many domains of cognition. This Center includes eight projects dedicated to various aspects of cognition and various general issues that arise in the effort to build explicit models that capture different aspects of cognition, and also includes an administrative core to help foster integration and provide computing resources. * Project 1: Functional and Neural Organization of Semantic Memory * Project 2: Interactive Processes in Language: Lexical Processing * Project 3: Interactive Processes in Language: Sentence Processing * Project 4: Mechanisms of Cognitive Control * Project 5: Interactive Processes in Perception: Neurophysiology of Figure-Ground Organization * Project 6: Basic Mechanisms and Cooperating Systems in Learning Memory * Project 7: Age and Experience Dependent Processes in Learning * Project 8: Theoretical Foundations * Core: Integration, Computational Resources, and Administration

Proper citation: NIMH Interdisciplinary Behavioral Science Center (RRID:SCR_008085) Copy   

•   Source: SciCrunch Registry

http://www.adrc.pitt.edu/

A research center associated with the University of Pittsburgh that specializes in the diagnosis of Alzheimer's disease and related disorders. The overall objective of the ADRC is to study the pathophysiology of Alzheimer's disease, with the aim of improving the reliability of diagnosis of Alzheimer's and developing effective treatment strategies. Current research foci emphasize neuropsychiatry and neuropsychology, molecular genetics and epidemiology, basic neuroscience, and structural and functional imaging that aid in the diagnosis and treatment of Alzheimer's disease. Specific services at the ADRC include: comprehensive diagnostic evaluation of patients with suspected Alzheimer's disease and other forms of dementia; evaluation of memory, language, judgment, and other cognitive abilities; and education and counseling for patients and families.

Proper citation: University of Pittsburgh Alzheimer Disease Research Center (RRID:SCR_008084) Copy   

•   Source: SciCrunch Registry

http://brainspan.org/

Atlas of developing human brain for studying transcriptional mechanisms involved in human brain development. Consists of RNA sequencing and exon microarray data profiling up to sixteen cortical and subcortical structures across full course of human brain development, high resolution neuroanatomical transcriptional profiles of about 300 distinct structures spanning entire brain for four midgestional prenatal specimens, in situ hybridization image data covering selected genes and brain regions in developing and adult human brain, reference atlas in full color with high resolution anatomic reference atlases of prenatal (two stages) and adult human brain along with supporting histology, magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) data.

Proper citation: Allen Human Brain Atlas: BrainSpan (Atlas of the Developing Brain) (RRID:SCR_008083) Copy   

•   Source: SciCrunch Registry

http://stroke.nih.gov/

Campaign to help educate the public about the symptoms of stroke and the importance of getting to the hospital quickly, with a wide range of materials about stroke prevention, treatment, and rehabilitation available through the site. The campaign includes outreach to consumers and health care professionals using mass media, grassroots outreach, partnerships, and community education.

Proper citation: Know Stroke Campaign (RRID:SCR_008073) Copy   

•   Source: SciCrunch Registry

http://www.dnaftb.org/dnaftb/

An animated primer on the basics of DNA, genes, and heredity organized around three key concepts: Classical Genetics, Molecules of Genetics, and Genetic Organization and Control. The science behind each concept is explained by: animation, image gallery, video interviews, problem, biographies, and links.

Proper citation: DNA From The Beginning: AN Animated Primer on the Basics of DNA, Genes, and Heredity (RRID:SCR_008028) Copy   

•   Source: SciCrunch Registry

http://www.genome.wisc.edu/

The E. coli Genome Project has the goal of completely sequencing the E. coli and human genomes. They began isolation of an overlapping lambda clonebank of E. coli K-12 strain MG1655. Those clones served as the starting material in our initial efforts to sequence the whole genome. Improvements in sequencing technology have since reached the point where whole-genome sequencing of microbial genomes is routine, and the human genome has in fact been completed. They initiated additional sequencing efforts, concentrating on pathogenic members of the family Enterobacteriaceae -- to which E. coli belongs. They also began a systematic functional characterization of E. coli K-12 genes and their regulation, using the whole genome sequence to address how the over 4000 genes of this organism act together to enable its survival in a wide range of environments.

Proper citation: E. coli Genome project (RRID:SCR_008139) Copy   

•   Source: SciCrunch Registry

http://organelledb.lsi.umich.edu/

Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light.

Proper citation: Organelle DB (RRID:SCR_007837) Copy   

•   Source: SciCrunch Registry