Shaokun (Stella) An

Shaokun (Stella) An

she/her

Postdoc at Brigham and Women's Hospital, developing computational methods for disease research using single-cell data.

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publications

TSEE: an elastic embedding method to visualize the dynamic gene expression patterns of time series single-cell RNA sequencing data

Published in BMC Genomics, 2019

This paper presents TSEE, an elastic embedding method to visualize dynamic gene expression patterns in time series single-cell RNA sequencing data.

Recommended citation: An S, Ma L, Wan L. (2019). "TSEE: an elastic embedding method to visualize the dynamic gene expression patterns of time series single-cell RNA sequencing data." BMC Genomics. 20: 77-92.
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DensityPath: an algorithm to visualize and reconstruct cell state-transition path on density landscape for single-cell RNA sequencing data

Published in Bioinformatics, 2019

This paper introduces DensityPath, an algorithm to visualize and reconstruct cell state-transition paths on density landscapes for single-cell RNA sequencing data.

Recommended citation: Chen Z, An S, Bai X, et al. (2019). "DensityPath: an algorithm to visualize and reconstruct cell state-transition path on density landscape for single-cell RNA sequencing data." Bioinformatics. 35(15): 2593-2601.
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A New Context Tree Inference Algorithm for Variable Length Markov Chain Model with Applications to Biological Sequence Analyses

Published in Journal of Computational Biology, 2022

This paper introduces a new context tree inference algorithm for Variable Length Markov Chain Model, with applications in biological sequence analyses.

Recommended citation: An S, Ren J, Sun F, et al. (2022). "A New Context Tree Inference Algorithm for Variable Length Markov Chain Model with Applications to Biological Sequence Analyses." Journal of Computational Biology. 29(8): 839-856.
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