Tracing cancer evolution and heterogeneity using Hi-C Dan D. Erdmann-Pham*, Sanjit S. Batra*, Timothy K. Turkalo, James Durbin, Marco
Blanchette, Iwei Yeh, Hunter Shain, Boris C. Bastian, Yun S. Song, Daniel S.
Rokhsar, Dirk Hockemeyer
To appear in Nature Communications (2023) [bioRxiv preprint here]
Transferability of Geometric Patterns from Protein Self-Interactions to
Protein-Ligand Interactions Antoine Koehl*, Milind Jagota*, Dan D. Erdmann-Pham*, Alexander Fung, Yun S.
Song Pacific Symposium on Biocomputing (2021). [bioRxiv preprint here]
RNA-Sieve: A likelihood-based deconvolution of bulk gene
expression data using single-cell references Dan D. Erdmann-Pham*, Jonathan Fischer*, Justin Hong, Yun S.
Song Genome
Research (2021). [bioRxiv preprint here] [software here]
EGGTART: A computational tool to visualize the dynamics of
biophysical transport processes via the inhomogeneous
ℓ-TASEP Dan D. Erdmann-Pham*, Wonjun Son*, Khanh Dao Duc, Yun S.
Song Biophysical Journal (2021). [arXiv preprint here] [software here]
The key parameters that govern translation efficiency Dan D. Erdmann-Pham, Khanh Dao Duc, Yun S. Song Cell
Systems 10(2) (2020). [arXiv preprint here]
[slides
here]
Singular Value Homogenization: A simple preconditioning
technique for linearly constrained optimization and its
potential applications in medical therapy Dan D. Erdmann-Pham, Aviv Gibali, Karl-Heinz Küfer, Philip Süss Journal
of Mathematics in Industry 6 (2016)
Preprints
Exact and efficient multivariate two-sample tests through adaptive linear
multi-rank statistics Dan D. Erdmann-Pham
[arXiv preprint
here] [software here]
[slides here]
Generalized Spacing-Statistics and a New Family of
Non-Parametric Tests Dan D. Erdmann-Pham, Jonathan Terhorst, Yun S. Song
Submitted. [arXiv preprint
here] [slides here]
Thesis
Probabilistic Models and Statistical Tools for Gene
Expression Analysis Dan D. Erdmann-Pham Ph.D. Dissertation