Author

Patrick A. Newbury

Michigan State UniversityORCID 0000-0002-3756-1747Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Assay:bulk RNA-seq· 2 Research Focus:drug response / drug discovery· 2 Organism:human· 2 Research Focus:database / resource· 1 Research Focus:differential expression· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Bin CheniD· 3 shared Benjamin Scott GlicksbergiD· 2 shared Billy ZengiD· 2 shared Anita WeniD· 1 shared Caven Chow· 1 shared Eran R. AndrechekiD· 1 shared Evgeny Chekalin· 1 shared Haiyan HuangiD· 1 shared

Activity by Year

2018-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 32 mutual co-author links

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3 shared papersBioinformatics

Bin ChenORCID

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Author profile →

3 papers

Recent·Most cited

OCTAD: an open workplace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features

Billy Zeng, Benjamin Scott Glicksberg, Patrick A. Newbury, Evgeny Chekalin, Jing Xing, Ke Liu, Anita Wen, Caven Chow, Bin Chen

OCTAD enables virtual screening of therapeutics for cancer patient groups using gene expression features, prioritizing potent drug candidates for experimental testing.

Nature Protocols · Dec 23, 2020Peer-reviewedBioinformatics

Evaluating cell lines as models for metastatic cancer through integrative analysis of open genomic data

Ke Liu, Patrick A. Newbury, Benjamin Scott Glicksberg, Billy Zeng, Shreya Paithankar, Eran R. Andrechek, Bin Chen

This study evaluates the genomic similarity between breast cancer cell lines and metastatic samples, finding significant differences and highlighting organoids as better models.

Nature Communications · May 15, 2019Peer-reviewedBioinformatics

AICM: A Genuine Framework for Correcting Inconsistency Between Large Pharmacogenomics Datasets

Zhiyue Tom Hu, Yuting Ye, Patrick A. Newbury, Haiyan Huang, Bin Chen

The paper introduces a framework to correct inconsistencies in pharmacogenomics datasets by improving drug-wise correlations while preserving cell-wise consistency.

Pacific Symposium on Biocomputing (PSB) · Nov 1, 2018Peer-reviewedBioinformatics