Author

Brian Lee

Simon Fraser University

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

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Biology Disciplines

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Bioinformatics· 2 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:differential expression· 2 Approach:machine learning (classical)· 2 Assay:whole-genome sequencing· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Aditi Narayanan· 1 shared Alexander Wait ZaranekiD· 1 shared Andrew J. SaykiniD· 1 shared Benjamin Hitz· 1 shared Cédric ChauveiD· 1 shared Christos A. DavatzikosiD· 1 shared Cricket Sloan· 1 shared David Glick· 1 shared

Activity by Year

2016-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperBioinformatics

Aditi Narayanan

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Author profile →

3 papers

Recent·Most cited

Discovering Genetic Signatures Associated with Alzheimer's Disease in Tiled Whole Genome Sequence Data: Results from the Artificial Intelligence for Alzheimer's Disease (AI4AD) Consortium

Sarah Wait Zaranek, Alexander Wait Zaranek, Peter Amstutz, Jingxuan Bao, Jiong Chen, Tom Clegg, Hannah Craft, Taeho Jo, Brian Lee, Kwangsik T. Nho, Sophia I. Thomopoulos, Christos A. Davatzikos, Li Shen, Heng Huang, Paul M. Thompson, Andrew J. Saykin

The paper uses tiled whole genome sequence data to identify genetic signatures associated with Alzheimer's disease using machine learning methods.

medRxiv · Aug 1, 2024 · PreprintGenetic & Genomic Medicine

Geographic heterogeneity impacts drug resistance predictions in Mycobacterium tuberculosis

Guo Liang Gan, Matthew H. Nguyen, Elijah Willie, Mohammad H. Rezaie, Brian Lee, Cédric Chauve, Maxwell W. Libbrecht, Leonid Chindelevitch

This study uses machine learning on whole-genome sequencing data from multiple geographic regions to predict drug resistance in Mycobacterium tuberculosis, finding that performance varies across datasets due to geographical heterogeneity.

bioRxiv · Sep 17, 2020 · PreprintBioinformatics

SnoVault and encodeD: A novel object-based storage system and applications to ENCODE metadata

Benjamin Hitz, Laurence D Rowe, Nikhil Podduturi, David Glick, Ulugbek Baymuradov, Venkat Malladi, Esther Chan, Jean Davidson, Idan Gabdank, Aditi Narayanan, Kathrina Onate, Jason Hilton, Marcus Ho, Brian Lee, Stuart Miyasato, , J. Michael Cherry

The paper introduces SnoVault, a metadata storage system, and encodeD, a tool for genomic data storage, both designed for the ENCODE project's data management needs.

bioRxiv · Jul 29, 2016Bioinformatics