Probabilistic metabolite annotation using retention time prediction and meta-learned projections

HIGHLIGHTS

• who: Constantino A. Garcu00eda from the Department of Information Technology, Escuela Politu00e9cnica Superior, Universidad San Pablo CEU, Campus Montepru00edncipe, Boadilla del Monte have published the article: Probabilistic metabolite annotation using retention time prediction and meta-learned projections, in the Journal: (JOURNAL)
• what: Hyperparameter search for the models was performed with the Tree-structured Parzen Estimator (TPE) algorithm , and a nested cross-validation was used in the evaluation. To that end, this work proposes a Bayesian meta-learning approach to project the predicted RTs to a specific Chromatographic Method (CM) based on just a few identified . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.