Joint inference of discrete and continuous factors captures variability across and within cell types
We developed mixture model inference with discrete-coupled autoencoders (MMIDAS), an unsupervised variational framework that jointly learns discrete clusters and continuous cluster-specific ...
Directed evolution methods face trade-offs between the control of discrete approaches and the throughput of modern continuous systems. Here, we engineered a method called lytic selection and evolution ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results