Searching the RRID Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

Search

Type in a keyword to search

On page 13 showing 241 ~ 260 out of 292 results
Snippet view Table view Download 292 Result(s)
Click the to add this resource to a Collection
  • RRID:SCR_006212

https://www.braintest.org/brain_test/BrainTest

A portal of online studies that encourage community participation to tackle the most challenging problems in neuropsychiatry, including attention-deficit / hyperactivity disorder, schizophrenia, and bipolar disorder. Our approach is to engage the community and try to recruit tens of thousands of people to spend an hour of their time on our site. You folks will provide data in both brain tests and questionnaires, as well as DNA, and in return, we will provide some information about your brain and behavior. You will also be entered to win amazon.com gift cards. While large collaborative efforts were made in genetics in order to discover the secrets of the human genome, there are still many mysteries about the behaviors that are seen in complex neuropsychiatric syndromes and the underlying biology that gives rise to these behaviors. We know that it will require studying tens of thousands of people to begin to answer these questions. Having you, the public, as a research partner is the only way to achieve that kind of investment. This site will try to reach that goal, by combining high-throughput behavioral assessment using questionnaires and game-like cognitive tests. You provide the data and then we will provide information and feedback about why you should help us achieve our goals and how it benefits everyone in the world. We believe that through this online study, we can better understand memory and attention behaviors in the general population and their genetic basis, which will in turn allow us to better characterize how these behaviors go awry in people who suffer from mental illness. In the end, we hope this will provide better, more personalized treatment options, and ultimately prevention of these widespread and extremely debilitating brain diseases. We will use the data we collect to try to identify the genetic basis for memory and impulse control, for example. If we can achieve this goal, maybe we can then do more targeted research to understand how the biology goes awry in people who have problems with cognition, including memory and impulse control, like those diagnosed with ADHD, Schizophrenia, Bipolar Disorder, and Autism Spectrum Disorders. By participating in our research, you can learn about mental illness and health and help researchers tackle these complex problems. We can''t do it without your help.

Proper citation: Brain Test (RRID:SCR_006212) Copy   


http://intramural.nimh.nih.gov/gcap/index.htm

Schizophrenia related portal that aims to solve the mystery of genetic predisposition to psychosis, develop new methods for early diagnosis and prevention, and discover new treatments that will cure people suffering from it. Our objectives are to fully characterize: # neurobiological mechanisms related to susceptibility genes for schizophrenia and related clinical disorders; # genetic variation in aspects of cognition and emotionality associated with schizophrenia; and # small molecular targets for novel therapies. A unique feature of this Program is that its diverse scientific resources will be focused on a highly specific scientific agenda, that is to acquire the critical biological information about the susceptibility genes associated with schizophrenia and related illnesses. Our mission and goal, to understand the basic mechanisms of serious mental illness, has again guided us into new areas of research and to new insights. We have found evidence of new genes implicated in the cause of schizophrenia and involved in brain functions related to cognition and emotion and we have begun to explore how genes interact with each other and with the environment to individualize risk for these conditions. We are working now with over 20 genes related to schizophrenia. One of the key developments in our research over the past year has been the emergence of some targets for the development of novel therapeutics. We have discovered a new schizophrenia susceptibility gene, KCNH2, which represents the first clear target for the development of novel treatments. Just in this past year, for example, we published the first extensive statistical analysis of how schizophrenia genes may vary in their risk effects based on different genetic background (Nicodemus et al Hum Gen 2006), the first studies of schizophrenia genes interacting in effecting gene expression in brain (Lipska et al Hum Mol Genetics 2006a, Lipska et al Hum Mol Gen 2006 b); the first evidence that the mechanism of genetic association of NRG1 with schizophrenia involves a novel isoform of the gene in human brain (Law et al PNAS 2006), and the first evidence that MAOA may be linked to mood and impulse control because it effects critical mood regulatory neural networks (Meyer-Lindenberg et al PNAS 2006).

Proper citation: Genes Cognition and Psychosis Program (RRID:SCR_006292) Copy   


https://portal.brain-map.org/explore/classes/nomenclature

Framework for creating brain cell type nomenclature, and include examples using published datasets. System allows designation of cell types with or without hierarchical organization. Nomenclature convention initially applied to brain cells and types, is intended to encompass existing naming strategies used in publications across diverse research teams. Allows tracking of many different taxonomies, including those from different organ systems or across diverse areas of bioscience.

Proper citation: Common Cell Type Nomenclature (RRID:SCR_021124) Copy   


  • RRID:SCR_021635

    This resource has 1+ mentions.

https://palamaralab.github.io/software/argon/

Software tool as fast simulator of genetic data that samples from Discrete Time Wright Fisher process backwards in time. Used to simulate long chromosomes and large samples under DTWF, with computational time comparable to recent coalescent simulators.

Proper citation: ARGON (RRID:SCR_021635) Copy   


  • RRID:SCR_016739

    This resource has 10+ mentions.

https://github.com/hakyimlab/PrediXcan

Software tool to detect known and novel genes associated with disease traits and provide insights into the mechanism of these associations. Used to test the molecular mechanisms through which genetic variation affects phenotype.

Proper citation: PrediXcan (RRID:SCR_016739) Copy   


  • RRID:SCR_017099

http://pklab.med.harvard.edu/scde/pagoda.links.html

Software tool for analyzing transcriptional heterogeneity to detect statistically significant ways in which measured cells can be classified. Used to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability among measured cells.

Proper citation: PAGODA (RRID:SCR_017099) Copy   


  • RRID:SCR_017068

    This resource has 1+ mentions.

https://github.com/FeeLab/seqNMF

Software tool for unsupervised discovery of sequential structure. Used to detect sequences in neural data generated by internal behaviors, such as animal thinking or sleeping. Used for unsupervised discovery of temporal sequences in high dimensional datasets in neuroscience without reference to external markers.

Proper citation: seqNMF (RRID:SCR_017068) Copy   


  • RRID:SCR_017439

https://github.com/epurdom/clusterExperiment

Software open source R package for executing, evaluating and visualizing different clusterings of experimental data, including data from single cell RNA-Seq studies. Software for running and comparing different clusterings of single cell sequencing data.

Proper citation: clusterExperiment (RRID:SCR_017439) Copy   


  • RRID:SCR_017443

    This resource has 1+ mentions.

http://neuroproteomics.scs.illinois.edu/microMS.htm

Software Python platform for image guided Mass Spectrometry profiling. Provides graphical user interface for automatic cell finding and point based registration from whole slide images. Simplifies single cell analysis with feature rich image processing.

Proper citation: microMS (RRID:SCR_017443) Copy   


  • RRID:SCR_017457

    This resource has 1+ mentions.

https://www.ncbi.nlm.nih.gov/pubmed/28653482

Software tool to facilitate tractography based deep brain stimulation (DBS) electrode targeting within patient specific stereotactic coordinate system used in operating room.

Proper citation: StimVision (RRID:SCR_017457) Copy   


  • RRID:SCR_017462

https://github.com/YosefLab/FastProject

Software Python tool for low dimensional analysis of single-cell RNA-Seq data. Software package for two dimensional visualization of single cell data. Analyzes gene expression matrix and produces output report in which two-dimensional of data can be explored.

Proper citation: FastProject (RRID:SCR_017462) Copy   


  • RRID:SCR_017595

    This resource has 50+ mentions.

http://www.jwatcher.ucla.edu

Software Java tool for quantitative analysis of behavior. Used to address any theoretical problem that requires complex sequence of actions to be scored by human observer. Runs on microcomputer providing Java Virtual Machine[TM] and has been tested on Windows[TM] and Macintosh[TM] systems. Legacy version (version 0.9) works on older systems (Macintosh OS-9 and Windows-98), while Version 1.0 works well on Macintosh OS-X and Windows XP systems. JWatcher Video works best on Windows XP systems and has reduced functionality running in Macintosh OS-X. JWatcher-Palm can be used to acquire data on Palm OS[TM] equipped device and analyze it on your main computer.

Proper citation: JWatcher (RRID:SCR_017595) Copy   


  • RRID:SCR_018766

    This resource has 1+ mentions.

https://github.com/mne-tools/mne-bids/

Software Python package to link Brain Imaging Data Structure and MNE-Python software for analyzing neurophysiology data with goal to make analyses faster to code, more robust to errors, and easily shareable with colleagues. Provides programmable interface for BIDS datasets in electrophysiology with MNE-Python. Used for organizing electrophysiological data into BIDS format and facilitating their analysis.

Proper citation: MNE-BIDS (RRID:SCR_018766) Copy   


  • RRID:SCR_022601

    This resource has 1+ mentions.

https://github.com/denisecailab/minian

Software miniscope analysis pipeline that requires low memory and computational demand so it can be run without specialized hardware. Offers interactive visualization that allows users to see how parameters in each step of pipeline affect output.

Proper citation: Minian (RRID:SCR_022601) Copy   


  • RRID:SCR_023032

https://github.com/Cai-Lab-at-University-of-Michigan/nTracer

Software tool as plug-in for ImageJ software. Used for tracing microscopic images.

Proper citation: nTracer (RRID:SCR_023032) Copy   


  • RRID:SCR_015724

    This resource has 10+ mentions.

http://neuroexpresso.org/

Database of mouse brain cell type-specific gene expression datasets. NeuroExpresso is able to demonstrate the use of marker genes for acquiring cell type specific information from whole tissue expression.

Proper citation: NeuroExpresso (RRID:SCR_015724) Copy   


  • RRID:SCR_015766

    This resource has 50+ mentions.

http://schizconnect.org

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 6,2026. Platform for mediation and integration of schizophrenia neuroimaging-related databases. It provides access to federated databases, novel mediation software, and large-scale data-sharing features.

Proper citation: SchizConnect (RRID:SCR_015766) Copy   


http://marmosetbrain.org/

Brain connectivity atlas to create systematic, digital repository for data on connections between different cortical areas, in primate species. Data repository for connections between different cortical areas in marmoset monkeys. Allows access to data set and enables other interpretations of data, in light of future evolution of knowledge about marmoset cortex.

Proper citation: Marmoset Brain Connectivity Atlas (RRID:SCR_015964) Copy   


  • RRID:SCR_016147

    This resource has 10+ mentions.

https://www.intomics.com/inbio/map/#home

Database for investigating and visualizing protein-protein interactions. It aims to maintain coverage, quality, convenience, and transparency in the field of PPI research.

Proper citation: inBio Map (RRID:SCR_016147) Copy   


  • RRID:SCR_016216

    This resource has 1000+ mentions.

https://fmriprep.org

Software tool as robust preprocessing pipeline for functional MRI.Used for preprocessing of diverse fMRI data.

Proper citation: fMRIPrep (RRID:SCR_016216) Copy   



Can't find your Tool?

We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.

Can't find the RRID you're searching for? X
  1. Neuroscience Information Framework Resources

    Welcome to the NIF Resources search. From here you can search through a compilation of resources used by NIF and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that NIF has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.

  3. Logging in and Registering

    If you have an account on NIF then you can log in from here to get additional features in NIF such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into NIF you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Sources

    Here are the sources that were queried against in your search that you can investigate further.

  9. Categories

    Here are the categories present within NIF that you can filter your data on

  10. Subcategories

    Here are the subcategories present within this category that you can filter your data on

  11. Further Questions

    If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.

X