Author

Yaoyu E. Wang

Dana-Farber Cancer Institute

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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Bioinformatics· 1 Genetic & Genomic Medicine· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Assay:bulk RNA-seq· 2 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Approach:experimental assay· 1

Frequent Co-Authors

John F QuackenbushiD· 2 shared Alton Etheridge· 1 shared Amanda Courtright· 1 shared Andrea J. BarczakiD· 1 shared Antony Partensky· 1 shared Benjamin Haibe‐KainsiD· 1 shared Brian P. Lawney· 1 shared Cassandra C. Garbutt· 1 shared

Activity by Year

2017-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 17 mutual co-author links

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2 shared papersGenetic & Genomic Medicine

John F QuackenbushORCID

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3 papers

Recent·Most cited

MicroRNA-mRNA networks define translatable molecular outcome phenotypes in osteosarcoma.

Christopher B. Lietz, Cassandra C. Garbutt, William Thomas Barry, Vikram Deshpande, Yen‐Lin Chen, Santiago A. Lozano‐Calderón, Yaoyu E. Wang, Brian P. Lawney, David H. Ebb, Gregory Michael Cote, Zhenfeng Duan, Francis John Hornicek, Edwin Choy, G. Petur Nielsen, Benjamin Haibe‐Kains, , Dimitrios Spentzos

The paper identifies microRNA-mRNA networks associated with prognosis in osteosarcoma and validates their predictive value across independent datasets.

Scientific Reports · Mar 10, 2020Peer-reviewedGenetic & Genomic Medicine

WebMeV: A Cloud Platform for Analyzing and Visualizing Cancer Genomic Data

Yaoyu E. Wang, Lev Kutnetsov, Antony Partensky, Jalil Farid, John F Quackenbush

WebMeV provides a cloud-based platform for analyzing and visualizing cancer genomic data, enabling users to access and explore large datasets with advanced analysis tools.

Cancer Research · Oct 31, 2017Peer-reviewedBioinformatics

Accuracy, Reproducibility And Bias Of Next Generation Sequencing For Quantitative Small RNA Profiling: A Multiple Protocol Study Across Multiple Laboratories

MD Giraldez, Ryan M. Spengler, Alton Etheridge, PM Godoy, Andrea J. Barczak, Srimeenakshi Srinivasan, PL De Hoff, Kahraman Tanrıverdi, Amanda Courtright, Shu Lu, Joseph A. Khoory, R. Rubio, David H. Baxter, Tom A. P. Driedonks, HPJ Buermans, , Muneesh Tewari

This study evaluates the accuracy, reproducibility, and bias of small RNA-seq across five protocols and nine labs, finding protocol-specific bias that can be mitigated with adapters and computational corrections.

bioRxiv · May 17, 2017 · PreprintGenomics