Retention time prediction with message-passing neural networks

HIGHLIGHTS

• who: Sergey Osipenko and colleagues from the Center for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Nobel Str, , Moscow, Russia have published the research work: Retention Time Prediction with Message-Passing Neural Networks, in the Journal: Separations 2022, 291 of /2022/
• what: The authors evaluate capabilities of message-passing neural networks (MPNN) that have demonstrated outstanding performance on many chemical tasks to accurately predict retention times. The authors implement a transfer learning pipeline with pretraining MPNN on the SMRT dataset and fine-tuning on several available and in-house . . .
  

   

  

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