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Methods in Molecular Biology (Clifton, N.J.)|June 25, 2022
MuSE: A Novel Approach to Mutation Calling with Sample-Specific Error ModelingShuangxi Ji, Matthew D Montierth, Wenyi Wang
Nature Reviews. Cancer|December 2, 2025
A guide to transcriptomic deconvolution in cancerYaoyi Dai, Shuai Guo, Yidan Pan, et al.
International Journal of Environmental Research and Public Health|April 3, 2021
The Impact of Multiple Sclerosis Disease Status and Subtype on Hematological ProfileJacob M Miller, Jeremy T Beales, Matthew D Montierth, et al.
Plos One|January 22, 2021
Contribution of viral infection to risk for cancer in systemic lupus erythematosus and multiple sclerosisDeborah K Johnson, Kaylia M Reynolds, Brian D Poole, et al.
Nucleic Acids Research|November 22, 2023
Reactivation of the G1 enhancer landscape underlies core circuitry addiction to SWI/SNFKaterina Cermakova, Ling Tao, Milan Dejmek, et al.
Biorxiv : the Preprint Server for Biology|December 15, 2025
Deconvolution of Sparse-count RNA Sequencing Data for Tumor Cells Using Embedded Negative Binomial DistributionsMatthew D Montierth, Hao Yan, Liyang Xie, et al.
Biorxiv : the Preprint Server for Biology|May 18, 2026
Scalable subclonal reconstruction of cancer cells in DNA sequencing data using a penalized likelihood modelYujie Jiang, Matthew D Montierth, Yu Ding, et al.
Biorxiv : the Preprint Server for Biology|July 15, 2024
Pan-cancer subclonal mutation analysis of 7,827 tumors predicts clinical outcomeYujie Jiang, Matthew D Montierth, Kaixian Yu, et al.
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