Author

Bang Wong

Broad 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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Genomics· 2 Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 3 Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:differential expression· 2 Organism:human· 2 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1

Frequent Co-Authors

Aravind SubramanianiD· 2 shared Arthur Liberzon· 2 shared Jesse S. BoehmiD· 2 shared Rajiv Narayan· 2 shared Ted Natoli· 2 shared Akl C. FahediD· 1 shared Alice H. BergeriD· 1 shared Alykhan F. Shamji· 1 shared

Activity by Year

2014-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersGenomics

Aravind SubramanianORCID

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Author profile →

4 papers

Recent·Most cited

Design and user experience testing of a polygenic score report: a qualitative study of prospective users

Deanna Brockman, Lia Petronio, Jacqueline S. Dron, Bum Chul Kwon, Trish Vosburg, Lisa Nip, Andrew Tang, Mary O’Reilly, Niall J. Lennon, Bang Wong, Kenney Ng, Katherine H Huang, Akl C. Fahed, Amit V. Khera

The paper designs and tests a polygenic score report for coronary artery disease, identifying user preferences for visual elements, risk communication, and personalized resources.

BMC Medical Genomics · Oct 1, 2021Peer-reviewedGenetic & Genomic Medicine

GeNets: A unified web platform for network-based analyses of genomic data

Taibo Li, April Kim, Joseph Rosenbluh, Heiko Horn, Liraz Greenfeld, David An, Andrew R. Zimmer, Arthur Liberzon, Jon Bistline, Ted Natoli, Yang Li, Aviad Tsherniak, Rajiv Narayan, Aravind Subramanian, Ted Liefeld, , Kasper Lage

GeNets provides a platform to compare genomic networks using machine learning and allows analysis of genetic and RNA sequencing data.

Nature Methods · Jun 15, 2018Peer-reviewedGenomics

A Next Generation Connectivity Map: L1000 Platform And The First 1,000,000 Profiles

Aravind Subramanian, Rajiv Narayan, Steven M. Corsello, David D. Peck, Ted Natoli, Xiaodong Lü, Joshua Gould, John F. Davis, Andrew A. Tubelli, Jacob K. Asiedu, David L. Lahr, Jodi Hirschman, Zihan Liu, Melanie K. Donahue, Bina Julian, , Todd R. Golub

The paper introduces the L1000 platform, a high-throughput gene expression profiling method, and reports 1.3 million perturbational profiles expanding the Connectivity Map for drug mechanism discovery and functional annotation.

Cell · Nov 1, 2017Peer-reviewedGenomics

Sashimi plots: Quantitative visualization of alternative isoform expression from RNA-seq data

Yarden Katz, Eric T Wang, Jacob Stilterra, Schraga Schwartz, Bang Wong, Helga Thorvaldsdóttir, James T Robinson, Jill P Mesirov, Edoardo M Airoldi, Christopher B Burge

The paper introduces Sashimi plots as a method to visualize and compare isoform expression across multiple RNA-Seq samples.

bioRxiv · Feb 11, 2014Bioinformatics