FLIGHTED: Inferring fitness landscapes from noisy high-throughput experimental data.
PubMed / NCBI E-utilities · 學術索引收錄 · 來源發佈：Fri Oct 02 2026 00:00:00 GMT+0000 (Coordinated Universal Time) · 本站收錄：Thu Oct 08 2026 09:09:22 GMT+0000 (Coordinated Universal Time)
已保存的原文節選
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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