Publications

Ontology-aware DNA methylation classification with a curated atlas of human tissues and cell types

Published in bioRxiv, 2025

We assemble the largest and most diverse atlas of exclusively healthy human tissue and cell samples profiled by 450K arrays, comprising of 16,959 samples across 86 tissues and cell types. Leveraging this resource, we introduce an ontology-aware classification framework that identifies robust CpG features associated with tissue and cell identity while integrating known anatomical and functional relationships.

Recommended citation: Mirae Kim, Ruth Dannenfelser, Yufei Cui, Genevera Allen, Vicky Yao bioRxiv 2025.04.18.649618; doi: https://doi.org/10.1101/2025.04.18.649618 https://doi.org/10.1101/2025.04.18.649618

Deep learning-based classification of breast cancer cells using transmembrane receptor dynamics

Published in Bioinformatics, 2022

Here we employ deep learning to classify breast cancer cell types based on the trajectories of epidermal growth factor receptor (EGFR)

Recommended citation: Mirae Kim, Soonwoo Hong, Thomas E Yankeelov, Hsin-Chih Yeh, Yen-Liang Liu, Deep learning-based classification of breast cancer cells using transmembrane receptor dynamics, Bioinformatics, Volume 38, Issue 1, January 2022, Pages 243–249, https://doi.org/10.1093/bioinformatics/btab581 https://academic.oup.com/bioinformatics/article/38/1/243/6352489

Transmembrane Receptor Dynamics as Biophysical Markers for Assessing Cancer Cells

Published in Handbook of Single-Cell Technologies, 2021

This book chapter is about Transmembrane Receptor Dynamics

Recommended citation: Kim, M., Liu, YL. (2022). Transmembrane Receptor Dynamics as Biophysical Markers for Assessing Cancer Cells. In: Santra, T.S., Tseng, FG. (eds) Handbook of Single-Cell Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-10-8953-4_38 https://link.springer.com/content/pdf/10.1007/978-981-10-8953-4_38.pdf

Three-dimensional two-color dual-particle tracking microscope for monitoring DNA conformational changes and nanoparticle landings on live cells

Published in ACS Nano, 2020

Here, we present a three-dimensional two-color dual-particle tracking (3D-2C-DPT) technique that can simultaneously localize two spectrally distinct targets in three dimensions with a time resolution down to 5 ms.

Recommended citation: Liu, Y.-L., Perillo, E. P., Ang, P., Kim, M., Nguyen, D. T., Blocher, K., Chen, Y.-A., Liu, C., Hassan, A. M., Vu, H. T., Chen, Y.-I., Dunn, A. K., & Yeh, H.-C. (2020). Three-Dimensional Two-Color Dual-Particle Tracking Microscope for Monitoring DNA Conformational Changes and Nanoparticle Landings on Live Cells. ACS Nano 14(7) 7927–7939. https://doi.org/10.1021/acsnano.9b08045 https://pubs.acs.org/doi/abs/10.1021/acsnano.9b08045

Spatial EGFR dynamics and metastatic phenotypes modulated by upregulated EphB2 and Src pathways in advanced prostate cancer

Published in Cancers, 2019

Recommended citation: Liu Y-L, Horning AM, Lieberman B, Kim M, Lin C-K, Hung C-N, Chou C-W, Wang C-M, Lin C-L, Kirma NB, et al. Spatial EGFR Dynamics and Metastatic Phenotypes Modulated by Upregulated EphB2 and Src Pathways in Advanced Prostate Cancer. Cancers. 2019; 11(12):1910. https://doi.org/10.3390/cancers11121910 https://www.mdpi.com/2072-6694/11/12/1910

Assessing metastatic potential of breast cancer cells based on EGFR dynamics

Published in Scientific reports, 2019

Using single-particle tracking techniques, we developed a phenotyping asssay named Transmembrane Receptor Dynamics (TReD), studied the dynamics of epidermal growth factor receptor (EGFR) in seven breast epithelial cell lines.

Recommended citation: Liu, YL., Chou, CK., Kim, M. et al. Assessing metastatic potential of breast cancer cells based on EGFR dynamics. Sci Rep 9, 3395 (2019). https://doi.org/10.1038/s41598-018-37625-0 https://www.nature.com/articles/s41598-018-37625-0