Author

L. D. Stein

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

Signature Assays, Organisms & Methods

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Organism:human· 3 Research Focus:cell type annotation· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Research Focus:chromatin & epigenetic regulation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1

Frequent Co-Authors

A. Danyi· 1 shared A. Murison· 1 shared C. M. Spring· 1 shared C. van Herpen· 1 shared D. Thompson· 1 shared E. Cuppen· 1 shared E. Lapouble· 1 shared G. Atwal· 1 shared

Activity by Year

2017-2019 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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1 shared paperCancer Biology

A. Danyi

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Author profile →

3 papers

Recent·Most cited

Exosomes transmit retroelement RNAs to drive inflammation and immunosuppression in Ewing Sarcoma

V. Evdokimova, P. Ruzanov, H. Gassmann, H. H. Zaidi, V. Peltekova, L. E. Heisler, J. D. McPherson, M. Orlic-Milacic, K. Specht, K. Steiger, S. J. Schober, U. Thiel, T. D. McKee, M. Zaidi, C. M. Spring, , P. H. Sorensen

This study identifies retroelement RNAs in Ewing Sarcoma exosomes that induce inflammation and immunosuppression in recipient cells.

bioRxiv · Oct 16, 2019 · PreprintCancer Biology

A deep learning system can accurately classify primary and metastatic cancers based on patterns of passenger mutations

W. Jiao, G. Atwal, P. Polak, R. Karlic, E. Cuppen, A. Danyi, J. de Ridder, C. van Herpen, M. P. Lolkema, N. Steeghs, G. Getz, Q. D. Morris, L. D. Stein, PCAWG Pathology & Clinical Correlates Working Grp, ICGC/TCGA Pan-cancer Analysis of Whole Genomes Net

This paper develops a deep learning classifier using whole genome sequencing data to distinguish cancer types and identify metastatic origins.

bioRxiv · Jan 22, 2019 · PreprintCancer Biology

Candidate cancer driver mutations in super-enhancers and long-range chromatin interaction networks

L. Wadi, L. Uuskula-Reimand, K. Isaev, S. Shuai, V. Huang, M. Liang, D. Thompson, Y. Li, L. Ruan, M. Paczkowska, M. Krassowski, I. Dzneladze, K. Kron, A. Murison, P. Mazrooei, , J. Reimand

The paper identifies 41 frequently mutated regulatory elements in cancer genomes, enriched in non-coding mutations and linked to gene expression control through chromatin interactions.

bioRxiv · Dec 19, 2017Cancer Biology