Author

Boqiang Tu

Massachusetts Institute of TechnologyORCID 0000-0002-3999-1986Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Synthetic Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:Bayesian inference· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1 Assay:proteomics· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Kevin M. EsveltiD· 2 shared Vikram SundariD· 2 shared Lindsey GuaniD· 1 shared

Activity by Year

2022-2024 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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2 shared papersBioinformatics

Kevin M. EsveltORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintMar 26, 2024

FLIGHTED: Inferring Fitness Landscapes from Noisy High-Throughput Experimental Data

Vikram Sundar, Boqiang Tu, Lindsey Guan, Kevin M. Esvelt

FLIGHTED improves protein fitness model performance by accounting for experimental noise in high-throughput data, showing that data size and architecture matter more than model scale.

4 citations

proteomicsBayesian inference

𝕏 PostBluesky

Synthetic BiologybioRxivPreprintMar 9, 2022

An ultra-high-throughput method for measuring biomolecular activities

Boqiang Tu, Vikram Sundar, Kevin M. Esvelt

This paper introduces DHARMA, an ultra-high-throughput method for measuring biomolecular activities, and benchmarks protein models using large variant datasets.

3 citations

statistical modelbenchmarking

𝕏 PostBluesky