You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Moss et al. (2020) (section 5.2 and appendix E) evaluate their algorithm using minimum free folding energy as an objective function in optimizing short proteins, deferring to ViennaRNA to compute the objective function in experiments. Here is an example where they call the RNAfold utility as a subprocess.
We acknowledge that [minimizing minimum free-fold energy] may not be biologically meaningful on its own, however, as free-folding energy is of critical importance to other down-stream genetic prediction tasks, we believe it to be a reasonable proxy for wet-lab-based genetic design loops.
I've worked with Tcellmatch (Fischer et al. 2020) before; it makes predictions based on short sequences (CDR3s), including variable length sequences. I believe @andrenguyen has some recent experience with this model also.
What are some open datasets for evaluation? These will be needed to answer #3 about hyperparameters and algorithms
cc @andrenguyen
The text was updated successfully, but these errors were encountered: