Author

Ting-I Lee

University of WashingtonORCID 0000-0002-4883-0199Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:differential expression· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Organism:C. elegans· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Joshua C. Russell· 2 shared Safiye ÇelikiD· 2 shared Su‐In LeeiD· 2 shared Anna E. SpiroiD· 1 shared Ben W. Blue· 1 shared Cezar Rangel PestanaiD· 1 shared Christopher Dirk KeeneiD· 1 shared Jennifer F. BobbiD· 1 shared

Activity by Year

2018-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersBioinformatics

Joshua C. Russell

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2 papers

Recent·Most cited

Principled Feature Attribution for Unsupervised Gene Expression Analysis

Joseph D. Janizek, Anna E. Spiro, Safiye Çelik, Ben W. Blue, Joshua C. Russell, Ting-I Lee, Matt Kaeberlin, Su‐In Lee

This paper introduces a novel unsupervised pathway attribution method that identifies major transcriptomic variation sources when combined with biologically-constrained models, applied to Alzheimer's disease brain samples.

bioRxiv · May 3, 2022 · PreprintBioinformatics

DECODER: A probabilistic approach to integrate big data reveals mitochondrial Complex I as a potential therapeutic target for Alzheimer’s disease

Safiye Çelik, Joshua C. Russell, Cezar Rangel Pestana, Ting-I Lee, Shubhabrata Mukherjee, Paul K. Crane, Christopher Dirk Keene, Jennifer F. Bobb, Matt R. Kaeberlein, Su‐In Lee

DECODER integrates large-scale gene expression data to identify mitochondrial Complex I as a therapeutic target for Alzheimer’s disease.

bioRxiv · Jul 23, 2018 · PreprintSystems Biology