Author

Tamaki Kobayashi

Johns Hopkins UniversityORCID 0000-0002-6908-4519Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:batch correction / integration· 1 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Assay:protein structure· 1 Assay:proteomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Amy WesolowskiiD· 2 shared Douglas Eric NorrisiD· 2 shared Ingo RuczinskiiD· 2 shared Sophie BérubéiD· 2 shared Thomas A. LouisiD· 2 shared William John MossiD· 2 shared

Activity by Year

2021-2023 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

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2 shared papersBioinformatics

Amy WesolowskiORCID

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2 papers

Recent·Most cited

BioinformaticsStatistics in MedicinePeer-reviewedMar 5, 2023

A Bayesian Hierarchical Model for Signal Extraction from Protein Microarrays

Sophie Bérubé, Tamaki Kobayashi, Amy Wesolowski…·Thomas A. Louis

The paper develops a Bayesian hierarchical model to extract posterior distributions and ranks from protein microarray data, showing improved performance over existing methods.

4 citations

protein structureBayesian inference

𝕏 PostBluesky

BioinformaticsPROTEOMICSPeer-reviewedOct 20, 2021

A Pre-Processing Pipeline to Quantify, Visualize andReduce Technical Variation in Protein Microarray

Sophie Bérubé, Tamaki Kobayashi, Amy Wesolowski…·Thomas A. Louis

The paper develops a pre-processing pipeline to correct technical variation in protein microarrays, showing that preprocessing impacts downstream analysis validity.

7 citations

proteomicsstatistical model

𝕏 PostBluesky