FLIGHTED: Inferring fitness landscapes from noisy high-throughput experimental data.
PubMed / NCBI E-utilities · Indexed academic record · Source published: Fri Oct 02 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · Indexed here: Thu Oct 08 2026 09:09:22 GMT+0000 (Coordinated Universal Time)
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Machine learning (ML) for protein design requires large protein fitness datasets generated by high-throughput experiments for training and benchmarking models. However, most models do not account for experimental noise inherent in these datasets, thereby harming model performance. Here, we develop fitness landscape inference generated by high-throughput experimental data (FLIGHTED), a Bayesian met
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