Published in bioRxiv, 2025
This paper presents scCausalVI, a causality-aware generative to learn cell-state-specific treatment effects to external stimulations. By incorporating structural causal modeling with cross-condition in silico prediction, scCausalVI enables to infer gene expression profiles under hypothetical scenarios.
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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Published in GigaScience, 2020
This paper presents D-EE, a distributed software for visualizing intrinsic structure of large-scale single-cell data.
Recommended citation: An S, Huang J, Wan L. (2020). "D-EE: Distributed software for visualizing intrinsic structure of large-scale single-cell data." GigaScience. 9(11): giaa126.
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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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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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