Autoregressive LSTM and Transformer models achieve 98% top-1 accuracy predicting next eluting m/z bin from prior sequence features in lipidomics data across cohorts.
Metabolomics insights into pathophysiological mechanisms of inter- stitial cystitis.International Neurourology Journal, 18(3):106–114, 2014
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The Language of Elution: Autoregressive Prediction of the Next Feature in Untargeted LC-HRMS Lipidomics
Autoregressive LSTM and Transformer models achieve 98% top-1 accuracy predicting next eluting m/z bin from prior sequence features in lipidomics data across cohorts.