Schwartz R - Search Results

1

Machine Learning and Radiogenomics: Lessons Learned and Future Directions.

Kang J, Rancati T, Lee S, Oh JH, Kerns SL, Scott JG, Schwartz R, Kim S, Rosenstein BS. Kang J, et al. Among authors: schwartz r. Front Oncol. 2018 Jun 21;8:228. doi: 10.3389/fonc.2018.00228. eCollection 2018. Front Oncol. 2018. PMID: 29977864 Free PMC article. Review.

2

Response of an actin filament network model under cyclic stretching through a coarse grained Monte Carlo approach.

Kang J, Steward RL, Kim Y, Schwartz RS, LeDuc PR, Puskar KM. Kang J, et al. Among authors: schwartz rs. J Theor Biol. 2011 Apr 7;274(1):109-19. doi: 10.1016/j.jtbi.2011.01.011. Epub 2011 Jan 15. J Theor Biol. 2011. PMID: 21241710 Free PMC article.

3

Structurally governed cell mechanotransduction through multiscale modeling.

Kang J, Puskar KM, Ehrlicher AJ, LeDuc PR, Schwartz RS. Kang J, et al. Among authors: schwartz rs. Sci Rep. 2015 Feb 27;5:8622. doi: 10.1038/srep08622. Sci Rep. 2015. PMID: 25722249 Free PMC article.

4

Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective.

Kang J, Schwartz R, Flickinger J, Beriwal S. Kang J, et al. Among authors: schwartz r. Int J Radiat Oncol Biol Phys. 2015 Dec 1;93(5):1127-35. doi: 10.1016/j.ijrobp.2015.07.2286. Epub 2015 Nov 11. Int J Radiat Oncol Biol Phys. 2015. PMID: 26581149 Review.

5

Neural Network Deconvolution Method for Resolving Pathway-Level Progression of Tumor Clonal Expression Programs With Application to Breast Cancer Brain Metastases.

Tao Y, Lei H, Lee AV, Ma J, Schwartz R. Tao Y, et al. Among authors: schwartz r. Front Physiol. 2020 Sep 4;11:1055. doi: 10.3389/fphys.2020.01055. eCollection 2020. Front Physiol. 2020. PMID: 33013452 Free PMC article.

6

Interpretable deep learning for chromatin-informed inference of transcriptional programs driven by somatic alterations across cancers.

Tao Y, Ma X, Palmer D, Schwartz R, Lu X, Osmanbeyoglu HU. Tao Y, et al. Among authors: schwartz r. Nucleic Acids Res. 2022 Oct 28;50(19):10869-10881. doi: 10.1093/nar/gkac881. Nucleic Acids Res. 2022. PMID: 36243974 Free PMC article.

7

Automated deconvolution of structured mixtures from heterogeneous tumor genomic data.

Roman T, Xie L, Schwartz R. Roman T, et al. Among authors: schwartz r. PLoS Comput Biol. 2017 Oct 23;13(10):e1005815. doi: 10.1371/journal.pcbi.1005815. eCollection 2017 Oct. PLoS Comput Biol. 2017. PMID: 29059177 Free PMC article.

8

Deconvolution and phylogeny inference of structural variations in tumor genomic samples.

Eaton J, Wang J, Schwartz R. Eaton J, et al. Among authors: schwartz r. Bioinformatics. 2018 Jul 1;34(13):i357-i365. doi: 10.1093/bioinformatics/bty270. Bioinformatics. 2018. PMID: 29950001 Free PMC article.

9

Assessing the contribution of tumor mutational phenotypes to cancer progression risk.

Tao Y, Rajaraman A, Cui X, Cui Z, Chen H, Zhao Y, Eaton J, Kim H, Ma J, Schwartz R. Tao Y, et al. Among authors: schwartz r. PLoS Comput Biol. 2021 Mar 12;17(3):e1008777. doi: 10.1371/journal.pcbi.1008777. eCollection 2021 Mar. PLoS Comput Biol. 2021. PMID: 33711014 Free PMC article.

10

Optimizing design of genomics studies for clonal evolution analysis.

Srivatsa A, Schwartz R. Srivatsa A, et al. Among authors: schwartz r. Bioinform Adv. 2024 Dec 2;4(1):vbae193. doi: 10.1093/bioadv/vbae193. eCollection 2024. Bioinform Adv. 2024. PMID: 39678206 Free PMC article.

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