Author

J. S. Song

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 3 Biophysics· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:DNA methylation· 2 Research Focus:gene regulatory network inference· 2 Organism:human· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Assay:ChIP-seq· 1

Frequent Co-Authors

M. Hejna· 2 shared A. Basu· 1 shared A. Emad· 1 shared A. Jorapur· 1 shared A. Ranjan· 1 shared A. T. Epstein· 1 shared B. A. Baur· 1 shared B. Cieza· 1 shared

Activity by Year

2017-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 13 mutual co-author links

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2 shared papersBiophysics

M. Hejna

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

Measuring DNA mechanics on the genome scale

A. Basu, D. G. Bobrovnikov, Z. Qureshi, T. Kayikcioglu, T. T. Ngo, A. Ranjan, S. Eustermann, B. Cieza, M. Hejna, T. H. Rube, K.-P. Hopfner, C. Wolberger, J. S. Song, T. Ha

This paper develops loop-seq to measure DNA bendability genome-wide and finds sequence-encoded low bendability upstream of TSSs that influences nucleosome positioning and chromatin remodeling.

bioRxiv · Aug 17, 2020Biophysics

Knowledge-guided analysis of ‘omics’ data using the KnowEnG cloud platform

C. Blatti, A. Emad, M. J. Berry, L. Gatzke, M. Epstein, D. Lanier, P. Rizal, J. Ge, X. Liao, O. Sobh, M. Lambert, C. S. Post, J. Xiao, P. Groves, A. T. Epstein, , S. Sinha

KnowEnG is a cloud-based platform that provides tools for analyzing genomics data using knowledge-guided data-mining and machine learning, demonstrating its utility in cancer research.

bioRxiv · May 19, 2019Cancer Biology

Can cancer GWAS variants modulate immune cells in the tumor microenvironment?

Y. Zhang, M. Manjunath, J. Yan, B. A. Baur, S. Zhang, S. Roy, J. S. Song

This study investigates how a breast cancer GWAS variant may regulate immune cell gene expression in the tumor microenvironment, potentially affecting cancer progression.

bioRxiv · Dec 13, 2018Cancer Biology

High accuracy label-free classification of kinetic cell states from holographic cytometry

M. Hejna, A. Jorapur, J. S. Song, R. L. Judson

This paper develops a method to classify cell states from holographic cytometry data with high accuracy, tracking responses to cancer therapeutics over time.

bioRxiv · Apr 14, 2017Cancer Biology