Author

Travis A. Canida

University of Maryland, College Park

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· 2

Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:Bayesian inference· 1 Assay:electronic health records· 1 Research Focus:fine-mapping· 1 Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1 Assay:imaging· 1 Approach:statistical model· 1

Frequent Co-Authors

Tianzhou MaiD· 2 shared Zhenyao YeiD· 2 shared Chen MoiD· 1 shared Hongjie Ke· 1 shared Hsin-Hsiung Huang· 1 shared Liyi Elliot HongiD· 1 shared Menglu LiangiD· 1 shared Peter V KochunoviD· 1 shared

Activity by Year

2021-2026 · peak 1/yr

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10 top collaborators · 30 mutual co-author links

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2 shared papersBioinformatics

Tianzhou MaORCID

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2 papers

Recent·Most cited

FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies

Travis A. Canida, Zhenyao Ye, Shao-Hsuan Wang, Hsin-Hsiung Huang, Yezhi Pan, Menglu Liang, Shuo Chen, Tianzhou Ma

FM-GPT is a Bayesian fine mapping method that identifies causal genes in phenome-wide transcriptome-wide association studies, improving accuracy and reducing false positives.

PLoS Genetics · Sep 8, 2026Peer-reviewedBioinformatics

A new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures

Chen Mo, Zhenyao Ye, Hongjie Ke, Tong Lu, Travis A. Canida, Song Liu, Qiong Wu, Zhiwei Zhao, Yizhou Ma, Liyi Elliot Hong, Peter V Kochunov, Tianzhou Ma, Shuo Chen

This paper introduces a new Mendelian Randomization method to estimate causal effects of multivariable brain imaging exposures and finds it outperforms existing methods in sensitivity, bias, and false discovery rate.

bioRxiv · Oct 1, 2021 · PreprintBioinformatics