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Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...

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Updated: Jun 12, 2026

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation
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ABCD-ReproNim: An educational program for responsible and reproducible analyses of ABCD data.

Angela R Laird1, Jessica E Bartley1, Julio A Peraza1

  • 1Department of Physics, Florida International University, Miami, FL, USA.

Developmental Cognitive Neuroscience
|June 10, 2026
PubMed
Summary
This summary is machine-generated.

ABCD-ReproNim offers training in responsible and reproducible analysis of Adolescent Brain Cognitive Development (ABCD) Study data. This course promotes skill development in efficient, re-executable design and FAIR data practices for researchers.

Keywords:
ABCDABCD-ReproNimHackathonReproNimResearch educational course

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Area of Science:

  • Neuroscience
  • Data Science
  • Educational Research

Background:

  • The Adolescent Brain Cognitive Development (ABCD) Study generates large-scale neuroimaging and behavioral data.
  • Reproducible research practices are crucial for validating findings in complex datasets.
  • Existing training gaps hinder researchers' ability to conduct reproducible analyses of the ABCD Study data.

Purpose of the Study:

  • To establish and deliver a comprehensive educational course, ABCD-ReproNim, for training researchers in responsible and reproducible data analysis.
  • To foster skill development in efficient, re-executable data analysis workflows and FAIR data practices.
  • To support interdisciplinary collaboration and disseminate best practices for analyzing ABCD Study data.

Main Methods:

  • A hybrid educational model combining a semester-long online didactic course with an in-person data analysis hackathon.
  • Curricular approach integrating active learning, inverted classrooms, and hack week methodologies.
  • Hands-on data exercises and team-based collaborative projects utilizing the ABCD Study dataset.

Main Results:

  • Over 1.1K students registered, with >18K YouTube views, indicating strong community reception.
  • Participants gain a comprehensive understanding of the ABCD dataset and reproducible research techniques.
  • The program successfully supports interdisciplinary collaborations and disseminates training materials.

Conclusions:

  • ABCD-ReproNim effectively addresses the need for specialized training in reproducible neuroimaging data analysis.
  • The course enhances the validity and reproducibility of research methods applied to the ABCD Study.
  • Graduates are equipped to conduct responsible, reproducible, and valid analyses, contributing to a new cadre of skilled investigators.