Poster | DeepiRT: Incorporating chromatography information boosts performance of iRT prediction model

DeepiRT: Incorporating chromatography information boosts performance of iRT prediction model

Poster presented at ASMS 2024, Anaheim (CA)

Neural networks have been extensively used in the proteomics field and their role on improving identifications is rapidly becoming more relevant. DeepiRT is a neural network designed to predict Indexed Retention Time (iRT) (Escher, 2012) for a given precursor based on its modified sequence.

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