Author

Punit Shah

Johns Hopkins University

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 Neuroscience· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Assay:proteomics· 3 Research Focus:differential expression· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Approach:experimental assay· 1 Organism:human· 1 Assay:metabolomics· 1

Frequent Co-Authors

Hui ZhangiD· 2 shared Ana Nicolle StratiD· 1 shared Bai ZhangiD· 1 shared Catherine J. PeñaiD· 1 shared Daniel W. ChaniD· 1 shared David J. ClarkiD· 1 shared Deena M. WalkeriD· 1 shared Drew D. KiralyiD· 1 shared

Activity by Year

2018-2018 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersBioinformatics

Hui ZhangORCID

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Author profile →

3 papers

Recent·Most cited

Multi-OMIC analysis of brain and serum from chronically-stressed mice reveals network disruptions in purine metabolism, fatty acid beta-oxidation, and antioxidant activity that are reversed by antidepressant treatment

Peter J. Hamilton, Emily Y. Chen, Vladimir Tolstikov, Catherine J. Peña, Punit Shah, Kiki Panagopoulos, Ana Nicolle Strat, Deena M. Walker, Zachary S. Lorsch, Nicholas L. Mervosh, Drew D. Kiraly, Rangaprasad Sarangarajan, Niven R. Narain, Michael A. Kiebish, Eric J. Nestler

The paper analyzes multi-omic data from stressed mice to identify molecular disruptions linked to depression and shows antidepressants reverse these changes in specific brain regions.

bioRxiv · Dec 8, 2018 · PreprintNeuroscience

MS-PyCloud: An open-source, cloud computing-based pipeline for LC-MS/MS data analysis

Li Chen, Bai Zhang, Michael Schnaubelt, Punit Shah, Paul Aiyetan, Daniel W. Chan, Hui Zhang, Zhen Zhang

MS-PyCloud is an open-source cloud-based pipeline for LC-MS/MS data analysis that provides scalable, reproducible, and efficient processing of proteomics data.

bioRxiv · May 13, 2018 · PreprintBioinformatics

Reanalysis of global proteomic and phosphoproteomic data identified a large number of glycopeptides

Yingwei Hu, Punit Shah, David J. Clark, Minghui Ao, Hui Zhang

The paper reanalyzes proteomic and phosphoproteomic data to identify a large number of previously unknown N-linked glycopeptides using GPQuest 2.0.

Analytical Chemistry · May 9, 2018Peer-reviewedSystems Biology