Author

R. Schwartz

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· 5 Biochemistry· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Organism:human· 4 Approach:statistical model· 4 Assay:whole-genome sequencing· 3 Research Focus:clustering· 2 Approach:deep learning· 2 Assay:bulk RNA-seq· 1 Research Focus:cell signaling & trafficking· 1 Research Focus:cell type annotation· 1

Frequent Co-Authors

J. Eaton· 2 shared A. Bushuiev· 1 shared A. C. Borczuk· 1 shared A. Kodra· 1 shared A. Rajaraman· 1 shared A. Ruiz· 1 shared A. Svoboda· 1 shared B. tenOever· 1 shared

Activity by Year

2018-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 9 mutual co-author links

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2 shared papersCancer Biology

J. Eaton

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Author profile →

7 papers

Recent·Most cited

Determining Optimal Placement of Copy Number Aberration Impacted Single Nucleotide Variants in a Tumor Progression History

C. H. Wu, S. Joshi, W. Robinson, P. F. Robbins, R. Schwartz, C. Sahinalp, S. Malikic

This paper introduces DETOPT, a method for accurately placing SNVs affected by CNAs in tumor progression trees, showing improved accuracy on simulated data and biologically plausible results on breast cancer metastases.

bioRxiv · Mar 10, 2024 · PreprintCancer Biology

Structure-enabled enzyme function prediction unveils elusive terpenoid biosynthesis in archaea

R. Samusevich, S. M. Akmese, T. Hebra, R. Bushuiev, M. Engst, J. Kulhanek, A. Bushuiev, J. D. Smith, T. Calounova, H. Smrckova, M. Molineris, R. Schwartz, A. Svoboda, R. Chatpatanasiri, S. C. Kampranis, , T. Pluskal

The paper introduces EnzymeExplorer, a machine-learning pipeline that predicts enzyme function, discovering new terpenoid synthases in archaea and expanding their known taxonomic distribution.

bioRxiv · Jan 29, 2024 · PreprintBiochemistry

Sc-TUSV-ext: Single-cell clonal lineage inference from single nucleotide variants (SNV), copy number alterations (CNA) and structural variants (SV)

N. A. Bristy, X. Fu, R. Schwartz

Sc-TUSV-ext improves clonal lineage reconstruction by integrating SNV, CNA, and SV from single-cell DNA sequencing data, showing better accuracy on synthetic and real data.

bioRxiv · Dec 7, 2023 · PreprintCancer Biology

Modeling the effect of spatial structure on solid tumor evolution and ctDNA composition

T. Rachman, D. Bartlett, W. Laframboise, P. Wagner, R. Schwartz, O. Carja

This study models how spatially variable cell death in solid tumors affects ctDNA composition and clonal representation, showing potential biases in liquid biopsy profiles.

bioRxiv · Nov 10, 2023 · PreprintCancer Biology

SARS-CoV-2 infection results in lasting and systemic perturbations post recovery

J. J. Frere, R. A. Serafini, K. D. Pryce, M. Zazhytska, K. Oishi, I. Golynker, M. Panis, J. Zimering, S. Horiuchi, D. A. Hoagland, R. Moller, A. Ruiz, J. B. Overdevest, A. Kodra, P. D. Canoll, , B. tenOever

This study compares short- and long-term systemic responses to SARS-CoV-2 and IAV in golden hamsters, finding persistent inflammation in olfactory tissues post-recovery.

bioRxiv · Jan 18, 2022Microbiology

Improving personalized prediction of cancer prognoses with clonal evolution models

Y. Tao, A. Rajaraman, X. Cui, Z. Cui, J. Eaton, H. Kim, J. Ma, R. Schwartz

This study develops a computational framework to predict cancer progression using mutator phenotypes derived from tumor phylogenies, showing improved predictive power over traditional clinical and driver-centric features.

bioRxiv · Sep 18, 2019 · PreprintCancer Biology

Deconvolution and phylogeny inference of structural variations in tumor genomic samples

J. Eaton, J. Wang, R. Schwartz

This paper introduces a method to infer tumor phylogeny and deconvolute structural variations from bulk genomic data, showing it works well on simulated and breast cancer data.

bioRxiv · Jan 30, 2018Cancer Biology