Author

Chris Lin

University of Washington

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· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Approach:contrastive learning· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1

Frequent Co-Authors

Ching-Hao WangiD· 1 shared Ethan WeinbergeriD· 1 shared Finnian Firth· 1 shared Glyn Bradley· 1 shared Jeremy L. EnglandiD· 1 shared Kalin VetsigianiD· 1 shared Lena Granovsky· 1 shared Su‐In LeeiD· 1 shared

Activity by Year

2023-2023 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 16 mutual co-author links

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1 shared paperGenomics

Ching-Hao WangORCID

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2 papers

Recent·Most cited

Isolating salient variations of interest in single-cell data with contrastiveVI

Ethan Weinberger, Chris Lin, Su‐In Lee

The paper introduces contrastiveVI, a method to disentangle shared and treatment-specific variations in scRNA-seq data, showing improved performance over existing methods in four datasets.

Nature Methods · Aug 7, 2023Peer-reviewedBioinformatics

Simple Causal Relationships in Gene Expression Discovered through Deep Learned Collective Variables

Ching-Hao Wang, Kalin Vetsigian, Chris Lin, Finnian Firth, Glyn Bradley, Lena Granovsky, Jeremy L. England

The paper develops a deep learning approach to identify simple causal relationships in gene expression by finding low-dimensional representations that predict genetic perturbation responses.

bioRxiv · Jan 18, 2023 · PreprintGenomics