Author

Philip Daniel Compton

Northwestern UniversityORCID 0000-0001-5212-7175Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Systems Biology· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Bryan P. Early· 1 shared Caroline J. DeHartiD· 1 shared Dan LüiD· 1 shared Deepesh Agarwal· 1 shared Galit LahaviD· 1 shared Jeremy GunawardenaiD· 1 shared Neil L. KelleheriD· 1 shared Paul M. ThomasiD· 1 shared

Activity by Year

2018-2018 · peak 1/yr

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9 top collaborators · 36 mutual co-author links

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1 shared paperSystems Biology

Bryan P. Early

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1 paper

Recent·Most cited

Analysing protein post-translational modform regions by linear programming

Deepesh Agarwal, Ryan T. Fellers, Bryan P. Early, Dan Lü, Caroline J. DeHart, Philip Daniel Compton, Paul M. Thomas, Galit Lahav, Neil L. Kelleher, Jeremy Gunawardena

The paper uses linear programming to estimate modform distributions of proteins with multiple post-translational modifications, showing that combining bottom-up and top-down MS data reduces average modform range.

bioRxiv · Oct 30, 2018 · PreprintSystems Biology