Liu, X. Shirley

Determinants of transcription factor regulatory range

Chen, C.-H., Zheng, R., Tokheim, C., Dong, X., Fan, J., Wan, C., Tang, Q., Brown, M., Liu, J. S., Meyer, C. A., et al. (2020) · Nature Communications

Genomics and Chromatin DynamicsGene Regulatory Network Analysis

Cited by 85

MIRA: joint regulatory modeling of multimodal expression and chromatin accessibility in single cells

Lynch, A. W., Theodoris, C. V., Long, H. W., Brown, M., Liu, X. S., & Meyer, C. A. (2022) · Nature Methods

Single-cell and spatial transcriptomicsGenomics and Chromatin Dynamics

Cited by 80

Machine learning modeling of protein-intrinsic features predicts tractability of targeted protein degradation

Zhang, W., Roy Burman, S. S., Chen, J., Donovan, K. A., Cao, Y., Zhang, B., Zeng, Z., Zhang, Y., Li, D., Fischer, E. S., et al. (2021) · Genomics Proteomics & Bioinformatics

Protein Degradation and InhibitorsComputational Drug Discovery Methods

Cited by 51

Target gene-specific regulation of androgen receptor activity by p42/p44 mitogen-activated protein kinase.

Agoulnik, I. U., Bingman, W. E., Nakka, M., Li, W., Wang, Q., Liu, X. S., Brown, M., & Nancy L., N. L. (2008) · Molecular Endocrinology

Prostate Cancer Treatment and ResearchEstrogen and related hormone effects

Cited by 36

Robust identification of perturbed cell types in single-cell RNA-seq data

Nicol, P. B., Paulson, D., Qian, G., Liu, X. S., Irizarry, R., & Sahu, A. D. (2023) · Nature Communications

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 33