6 citations · 9 across the 3 of their papers we have counts for
3 papers
PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design
Ji Won Park, Samuel Stanton, Saeed Saremi +6
Bayesian optimization offers a sample-efficient framework for navigating the exploration-exploitation trade-off in the vast design space of biological sequences. Whereas it is poss…
Multi-segment preserving sampling for deep manifold sampler
Daniel Berenberg, Jae Hyeon Lee, Simon Kelow +6
Deep generative modeling for biological sequences presents a unique challenge in reconciling the bias-variance trade-off between explicit biological insight and model flexibility.…
Deep learning models for predicting RNA degradation via dual crowdsourcing
Hannah K. Wayment-Steele, Wipapat Kladwang, Andrew M. Watkins +26
Messenger RNA-based medicines hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limite…