Author

Yun-En Chung

University of OttawaORCID 0000-0002-2029-8364Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Assay:protein sequence· 1 Research Focus:protein structure prediction· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Mathieu Lavallée‐AdamiD· 2 shared Alexander R. PelletieriD· 1 shared Amit K. ScheeriD· 1 shared Dallas Nygard· 1 shared Daniel FigeysiD· 1 shared Emily Hashimoto-RothiD· 1 shared Iryna AbramchukiD· 1 shared Nora Wong· 1 shared

Activity by Year

2020-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersBioinformatics

Mathieu Lavallée‐AdamORCID

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2 papers

Recent·Most cited

Computational identification of human biological processes and protein sequence motifs putatively targeted by SARS-CoV-2 proteins using protein-protein interaction networks

Rachel Nadeau, Soroush Shahryari Fard, Amit K. Scheer, Emily Hashimoto-Roth, Dallas Nygard, Iryna Abramchuk, Yun-En Chung, Steffany A. L. Bennett, Mathieu Lavallée‐Adam

The paper identifies human biological processes and protein sequence motifs potentially targeted by SARS-CoV-2 using PPI networks and computational methods.

Journal of Proteome Research · Oct 26, 2020Peer-reviewedBioinformatics

MealTime-MS: A Machine Learning-Guided Real-Time Mass SpectrometryAnalysis for Protein Identification and Efficient DynamicExclusion

Alexander R. Pelletier, Yun-En Chung, Zhibin Ning, Nora Wong, Daniel Figeys, Mathieu Lavallée‐Adam

MealTime-MS improves protein identification in mass spectrometry by using real-time supervised learning to reduce redundant data collection and enhance detection of low-abundance proteins.

Journal of the American Society for Mass Spectrometry · Jun 8, 2020Peer-reviewedBioinformatics