Author

Jonathan H. Huggins

Boston UniversityORCID 0000-0002-9256-6727Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Assay:whole-genome sequencing· 3 Organism:human· 2 Approach:statistical model· 2 Research Focus:variant calling· 2 Approach:Bayesian inference· 1 Research Focus:ecology & biodiversity· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

Joshua David CampbelliD· 2 shared Masanao YajimaiD· 2 shared Aaron A. ChevalieriD· 1 shared Cameron WebbiD· 1 shared Catherine XueiD· 1 shared Darren Jianjhih ChiuiD· 1 shared Dongchen ZhangiD· 1 shared Jeffrey W. MilleriD· 1 shared

Activity by Year

2021-2026 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 12 mutual co-author links

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2 shared papersBioinformatics

Joshua David CampbellORCID

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Author profile →

4 papers

Recent·Most cited

Robust discovery of mutational signatures using power posteriors

Catherine Xue, Jeffrey W. Miller, Scott L. Carter, Jonathan H. Huggins

This paper introduces a Bayesian NMF approach with power posteriors and sparsity-inducing priors to improve mutational signature discovery, showing better accuracy than existing methods.

PLoS Computational Biology · Jun 11, 2026Peer-reviewedBioinformatics

Defining mutational signatures of lung cancer-associated carcinogens through in vitro exposure of human airway epithelial cells

Natasha Q. Gurevich, Darren Jianjhih Chiu, Masanao Yajima, Jonathan H. Huggins, Sarah A. Mazzilli, Joshua David Campbell

This study uses in vitro exposure of human airway epithelial cells to genotoxic carcinogens to define mutational signatures associated with lung cancer.

bioRxiv · Mar 9, 2026 · PreprintBioinformatics

Mapping the North American Terrestrial Carbon Cycle: A Process-based Reanalysis Using State Data Assimilation (SDA)

Dongchen Zhang, Jonathan H. Huggins, Qianyu Li, Shashank Ramachandran, Shawn Paul Serbin, Cameron Webb, Zhenpeng Zuo, Michael C. Dietze

This study uses a hybrid state data assimilation framework to generate accurate carbon budget maps of North America, reducing uncertainties in carbon pools and identifying regional trends.

bioRxiv · Feb 26, 2026 · PreprintEcology

The Mutational Signature Comprehensive Analysis Toolkit (musicatk) for the discovery, prediction, and exploration of mutational signatures

Aaron A. Chevalier, Shiyi Yang, Zainab Khurshid, Nathan J Sahelijo, Tong Tong, Jonathan H. Huggins, Masanao Yajima, Joshua David Campbell

The paper introduces musicatk, a toolkit for analyzing mutational signatures, enabling preprocessing, analysis, visualization, and comparison to COSMIC database.

Cancer Research · Oct 8, 2021Peer-reviewedBioinformatics