Author

F.-Z. Li

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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Bioengineering· 2 Immunology· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:protein sequence· 2 Approach:deep learning· 1 Approach:experimental assay· 1 Research Focus:host-pathogen & immune response· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:protein design· 1

Frequent Co-Authors

Y. Yue· 2 shared A. D. Corrado· 1 shared A. Koide· 1 shared A. P. Amini· 1 shared A. X. Lu· 1 shared C. Diefenbach· 1 shared C. Wang· 1 shared F. H. Arnold· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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2 shared papersBioengineering

Y. Yue

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models

F.-Z. Li, A. P. Amini, Y. Yue, K. K. Yang, A. X. Lu

This study analyzes transfer learning in protein language models, finding that downstream task performance often relies on early pretraining features rather than scaling with pretraining duration.

bioRxiv · Feb 5, 2024 · PreprintBioengineering

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

J. Yang, J. Ducharme, K. E. Johnston, F.-Z. Li, Y. Yue, F. H. Arnold

DeCOIL optimizes degenerate codon libraries for ML-assisted protein engineering to generate diverse and high-fitness protein variants.

bioRxiv · May 11, 2023Bioengineering

Two-dimensional multiplexed assay for rapid and deep SARS-CoV-2 serology profiling and for machine learning prediction of neutralization capacity

A. Koide, T. Panchenko, C. Wang, S. A. Thannickal, L. A. Romero, K. W. Teng, F.-Z. Li, P. Akkapeddi, A. D. Corrado, J. Caro, C. Diefenbach, M. I. Samanovic, M. J. Mulligan, T. Hattori, K. A. Stapleford, , S. Koide

This paper introduces a 2D-MBBA assay for SARS-CoV-2 serology profiling and uses machine learning to predict neutralization capacity from antibody profiles.

bioRxiv · Aug 3, 2021 · PreprintImmunology