Author

Weston D. Viles

University of Southern Maine

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:gene regulatory network inference· 2 Organism:human· 2 Assay:metagenomics· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Assay:metabolomics· 1

Frequent Co-Authors

Anne Gatewood HoeniD· 3 shared Jiang GuiiD· 3 shared Jie Ming ZhouiD· 3 shared Juliette C. MadaniD· 3 shared Margaret Rita KaragasiD· 2 shared Boran Lu· 1 shared Erika F. Dade· 1 shared Haobin CheniD· 1 shared

Activity by Year

2020-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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3 shared papersBioinformatics

Anne Gatewood HoenORCID

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Author profile →

3 papers

Recent·Most cited

Identifying Microbial Interaction Networks Based on Irregularly Spaced Longitudinal 16S rRNA sequence data

Jie Ming Zhou, Jiang Gui, Weston D. Viles, Haobin Chen, Juliette C. Madan, Modupe Oluseun Coker, Anne Gatewood Hoen

The paper proposes a stationary Gaussian graphical model for microbial interaction networks using longitudinal 16S rRNA data and shows it outperforms conventional methods in correlated settings.

bioRxiv · Nov 26, 2021 · PreprintBioinformatics

Information Enhanced Model Selection for Gaussian Graphical Model with Application to Metabolomic Data

Jie Ming Zhou, Anne Gatewood Hoen, Susan McRitchie, Wimal Pathmasiri, Weston D. Viles, Quang P. Nguyen, Juliette C. Madan, Erika F. Dade, Margaret Rita Karagas, Jiang Gui

The paper introduces a method for selecting Gaussian graphical models using prior knowledge and applies it to metabolomic data, finding that metabolic pathways significantly influence metabolite dependencies.

Biostatistics · Jan 28, 2021Peer-reviewedBioinformatics

Estimating Microbial Interaction Network:Zero-inflated Latent Ising Model Based Approach

Jie Ming Zhou, Weston D. Viles, Boran Lu, Zhigang Li, Juliette C. Madan, Margaret Rita Karagas, Jiang Gui, Anne Gatewood Hoen

The paper introduces a zero-inflated latent Ising model to estimate microbial interaction networks, showing it outperforms traditional methods in simulated and real gut microbiome data.

BioData Mining · Oct 7, 2020Peer-reviewedBioinformatics