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deep neural network model coupled with graph attention network (GAT) and 1D-Transformer to predict Rention Time

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Frank-LIU-520/RT_Transformer_Smiles

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RT_Transformer_Smiles

Deep neural network model coupled with graph attention network (GAT) and 1D-Transformer to predict Rention Time.

The SMRT dataset from the METLIN library was used for pretraining.

Reference: (1) xue jun, Wang B, li W. RT-Tranformer: Retention Time Prediction for Metabolite Annotation to Assist in Metabolite Identification. ChemRxiv. Cambridge: Cambridge Open Engage; 2023; This content is a preprint and has not been peer-reviewed.

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deep neural network model coupled with graph attention network (GAT) and 1D-Transformer to predict Rention Time

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