Welcome to ImmunoPlex, a suite of tools for immunology data management, quality control, analysis and sharing

ImmunoPlex enables researchers to assess, analyze, and share data. ImmunoPlex improves QA and QC practices to make them accessible and standardized. We offer tools that enable discovery by increasing statistical power. ImmunoPlex promotes data interoperability, making research more transparent and data more reusable for the community.

Getting started with ImmunoPlex is easy. Based in Python, PostgreSQL, and R Shiny, ImmunoPlex is free, open-source and available through GitHub

 

Mobile data portal (MODAPO)

The ImmunoPlex Mobile Data Portal seamlessly integrates data sharing into research projects.  The integrated workflow system of the Data Portal addresses the complex challenge of transforming research database content into ImmPort-compliant submissions through a three-layer architecture that separates concerns while maintaining data integrity throughout the pipeline. The system is built around the official ImmPort data model and incorporates the requirements specified in the ImmPort Data Management and Sharing Plan template. Learn more here.

 

Interactive serology plate inspector (I-SPI)

I-SPI is an open-source web application designed to streamline quality control and quality assurance for multiplex immunoassays. It provides a unified workflow that supports both automation and user decision making while remaining grounded in objective statistical algorithms. Learn more here.

TEAM

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Annie Hoen, PhD

Annie completed her PhD in epidemiology and public health at Yale University and was a postdoctoral fellow at Harvard Medical School. She is currently an Associate Professor of Epidemiology, of Biomedical Data Science and of Microbiology & Immunology at the Geisel School of Medicine at Dartmouth. 

Hardik Gupta, MENG

Hardik is a Research Assistant III (Data Science) in the Hoen Lab at Dartmouth, where he builds research software and infrastructure spanning DevOps, data engineering, and machine learning to make complex biomedical datasets analysis-ready. He partners with biostatisticians to develop and maintain analysis tools and is actively exploring deep-learning approaches for feature extraction and predictive modeling.

Lily Macveagh, BA

Lily completed her bachelor's degree in Sociology at Hamilton College with a minor in French. She has been a Research Assistant in the Hoen Lab since 2024, working on data harmonization and data sharing.

FIONA MCENANY, MPH

Fiona is a microbiology and immunology PhD candidate. She graduated from The Dartmouth Institute for Health Policy and Clinical Practice with a Master of Public Health and Plymouth State University with degrees in biology and political science. She studies how gestational age at the time of maternal vaccination impacts maternal antibody response and neonatal transfer.

Seamus Stein, MS

Seamus is a front-end software developer and statistical analyst in the Hoen Lab. Prior to joining the department he earned his Master of Science in Quantitative Biomedical Sciences concentrating in health data science at Dartmouth College, and his Bachelor’s degree in Data Science with minors in Mathematics and Philosophy & Ethics at Saint Michael’s College.

Scot zens, PhD

Scot is a research scientist with expertise in the analysis of case/control data, survival analysis, and the pooling of studies to address questions in heterogeneous data. He also designs and implements systems for collecting, standardizing and providing quality control for all types of research data.

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JIE ZHOU, PHD

Jie completed his PhD in statistics and mathematics at Xidian University, China. He has worked as a reserach scientist at Dartmouth College since July 2018 with both the Hoen Lab and Professor Jiang Gui. He develops statistical tools such as time series models and graphical models to decipher complex relationships within the human microbiome and metabolome and associated health outcomes.

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