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ReproNim: A Center for Reproducible Neuroimaging Computation

Welcome to ReproNim!

ReproNim's goal is to improve the reproducibility of neuroimaging science and extend the value of our national investment in neuroimaging research, while making the process easier and more efficient for investigators.

ReproNim delivers a reproducible analysis framework comprised of components that include:

  • data and software discovery
  • implementation of standardized description of data, results and workflows
  • development of execution options that facilitates operation in all computational environments
  • provide training and education to the community

All components of the framework are intended to foster continued use and development of the reproducible and generalizable framework in neuroimaging research. See our Blog Post for more discussion of ReproLake and ReproPond.

Data flow diagram

Breaking News

  • NIH Office of Data Science Strategy : Data Sharing and Reuse Seminar Series, July 12, 2024, 12-1pm EDT
    • ReproNim faculty member Satra Ghosh discusses The Transformative Potential and Challenges of Open Data and Technologies in Neuroscience
    • Open to the Public, Registration required
  • OHBM 2024 | Organization for Human Brain Mapping Annual Meeting, June 23-27, 2024, Seoul, South Korea
  • ReproNim was at the 2024 Society of Biological Psychiatry (SOBP) Annual Meeting, May 9-11, 2024 (JW Marriott, Austin, Texas)
    • SOBP BrainHack, May 7-8, 2024, University of Texas Austin (in person)
      • ReproNim faculty, collaborators, colleagues and friends initiated a very productive two-day SOBP BrainHack event!
        • Hackathon: Open Collaboration on participant projects
        • Unconference: Presentations and Panel Content, organized on site by attendees
        • Learn: Basic software and Data Analysis Skills through live lectures, hands-on tutorials
        • Community Building: Meet, greet, socialize and network
    • SOBP Conference Symposium, Thursday, May 9, 2024 (JW Marriott, Austin, Texas)
  • Applications are now closed for the 2024 Neurohackademy summer school program in neuroimaging and data science based at the University of Washington eScience Institute, Seattle. This is a two-week program offered in hybrid format, July 29 – August 10, 2024). ReproNim faculty and collaborators are long time participants in this program!
    • Applications no longer being accepted
  • Congratulations and a big Welcome to our new 2024 ReproNim/INCF Fellowship Program Awardees!
  • ReproNim Webinar Series ~ Join us for our new Fall Season!
    • Webinars are held on the first Friday of every month during the academic year, from 2-3pm Eastern Time, and are open to the public.
    • Featured topics will include important efforts in reproducibility, from both ReproNim and others
      • Friday, October 4, 2024 at 2pm EDT
        • Our special guest speaker this month is Mike Milham, who joins us from the Child Mind Institute. Mike’s work spans brain development, child and adolescent psychiatry, and the advancement of neuroimaging data sharing initiatives and implementation of big data all in the service of understanding how functional & structural connectivity in brain may underlie mental illness. He discusses some of his very recent work with a presentation on "Moving beyond processing- and analysis-related variation in resting-state functional brain imaging."
        • Video Conference open to the public, Register in advance for videoconference connect details
        • Session will be recorded for those unable to attend, and both Slides and Video Presentation will be made available
      • Friday, September 6, 2024 at 2pm EDT
        • We are excited to kick off the new academic year with special guest speaker Chris Mungall! Chris joins us from Berkeley National Lab & Univ. California, where he leads the Biosystems Data Science group. Chris has very considerable expertise in large systems-level computation modeling, systems biology, data science, reusable and interoperable software, machine learning and knowledge graphs, and shares his remarkable perspective with a presentation on "Creating AI-ready datasets using LinkML and biomedical ontologies.
        • Video Presentation is now available
  • ReproNim Office Hours Program Drop-In for virtual Office Hours on the First Thursday of each month at 1pm Eastern Time, or contact us anytime by email at info@repronim.org to schedule a session.

    See our ReproNim Publications

    News Archive

    Use cases

    ReproNim tools and services are intended to support a wide range of users with varied background, from applied users with minimal or extensive experience in image analysis, physics, and computer science to technology developers and software engineers.

    Read more.

Discover

On-demand access (discovery) for widely distributed web-based data, publication and software resources, with highly refined search tools. There are two broad classes of product we envision:

  • Tools to help researchers Publish their data, making it discoverable
  • Tools to help researchers Discover published data.

These tools are designed to facilitate data sharing, use and discovery. ReproNim is developing an integrated application, NeuroBLAST, that will powerfully enable user-specified search and publish functions to data repositories, published studies, versioned software packages, study-related questions, and content.

Read more.

Describe

Reproducible description based on recording, reporting, and reusing experimenter procedures from start to finish. Machine-captured experimental metadata from scanner (data acquisition) to methods, analyses, and results.

  • Tools to help researchers record (describe) experimental procedures
  • Tools to help researchers define and semantically describe workflow.

ReproNim is developing BrainVerse to help researchers manage, track and share information in a comprehensive format.

Read more.

Do

Efficient management of data and scripts while capturing the history and details of changes and analyses execution in a fashion that facilitates inspection, comparison, modification, sharing, and re-execution. We provide

  • Support, maintenance, and promotion of platforms (e.g., NeuroDebian) and tools (e.g., Singularity and DataLad) for efficient and reproducible computation and data management
  • Tools and materials to establish reproducible computation across all stages of the neuroimaging research

ReproNim is developing ReproIn framework for turnkey collection of BIDS datasets straight from the scanner, and ReproMan to help researchers track and manage computation resources that they have available and to use them in a reproducible and scalable way.

Read more.

Teach

An increasing body of evidence point to some issues in reproducibility in biomedical or life sciences. The issue of lack of reproducibility has been now described in several scientific domains and for several years, raising concerns in the scientific community. ReproNim has developed a curriculum that will give researchers the information, tools and practices to perform repeatable and efficient research and a map of where to find the resources for deeper practical training.

Read more.

Tools

We have many tools designed to help the user work through a more reproducible version of their data analysis tasks. These toold support areas such as Data processing, Data ingestion, Standardization, Search, Data Management, Computation, Testing, etc.

Read more.

Community

ReproNim is only as successful as the neuroimaging community itself. We encourage active participation and engagement in our efforts. See our current community collaborator and service projects.

Join us! If you have a project that could benefit from a collaborative relationship with ReproNim let us know your interests and needs via email at info@repronim.org. Someone from ReproNim will be in touch to see how we can work together.

Community events

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Contact

Email us at info@repronim.org

Read our blog at https://repronim.wordpress.com/

Find us on Twitter at @ReproNim

Watch us on at YouTube

Catch up on our news in the ReproNim Newsletter

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