Analytics MIDB Service Hubs

Analytics Hub: Advancing our understanding of brain development by building confidence in data collection and analytical methods across research groups.

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Our Expertise

We are pioneers in creating open-source, publicly-available methods and analytic tools to improve the reliability and confidence in data analysis.

These methods can influence high-impact, hypothesis-driven research by direct collaboration with research groups or via open-source publicly-available access by interested researchers.

We also train the next generation of statisticians to engage in cutting-edge methods and interdisciplinary research.

Our Directors

Saonli Basu and Mark Fiecas

Saonli Basu, PhD Professor, Division of Biostatistics
Mark Fiecas, PhD Associate Professor, Division of Biostatistics

Our Team


Eric Feczko PhD, MBI
Assistant Professor
Department of Pediatrics


Oscar Miranda-Dominguez, PhD
Assistant Professor
Department of Pediatrics


David Schneck, MS
Research Associate

Long Tran

Long Tran, MS
Research Associate


Annette Xenopoulos-Oddsson, MSc
Project Manager

Lin Zhang

Lin Zhang, PhD
Interim Co-leader

Examples of Our Engagement

data sets

Open Source Tools for the Research Community UMN Genomic Data Commons

UMN Genomic Data Commons -  The Genomic Data Commons (GDC) is a central hub to store  both local and publicly available datasets, harmonize the genomic data and develop many analytical pipelines around these integrated databases. We will provide services that would facilitate genomic data storage, curation, integration, visualization, and downstream analysis. Learn more about the UMN Genomic Data Commons.

Students at MIDB

Outreach to K-12 Students

Beyond Walls  is a non-profit that supports economically disadvantaged youth in grades 6th-12th and the first four post secondary years through educational enrichment, health, and wellness through the sport of squash and civic leadership development. The Analytics Core hosts students onsite to introduce them to the application of math and biostatistics in neuroscience research.

graduate students

Graduate Student Training

In collaboration with the Interdisciplinary Biostatistics Training in Genetics and Genomics program funded by NIH T32 Training Grant: T32 GM132063, our core participates in the  training of graduate students in computational statistics. We provide training through journal club  participation and mentoring students on their  summer projects to develop analytic pipelines: 

  • Michael Anderson (Doctoral Student, Division of Biostatistics, School of Public Health): Mapping biological domains to ABCD mental health outcomes via Sparse PCA 
  • Christian Coffman (Doctoral Student, Division of Biostatistics, School of Public Health): Heritability of the variation in functional topology via adjHE
  • Mykhaylo Malakhov (Doctoral Student, Division of Biostatistics, School of Public Health): Development of RNAseq pipelines