A method for predicting one or more sample metric values by machine learning
AssigneeThermo Fisher Scientific (Bremen) GmbH
InventorKlaus Dennis Linke
Life of this patent
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Abstract
A method for predicting one or more sample metric values by machine learning is provided. The method comprises determining a plurality of characteristics from raw data obtained by analysing a proteomics sample in a liquid chromatography mass spectrometer, LC-MS. The method further comprises predicting one or more sample metric values by processing the plurality of characteristics using one or more trained machine learning models.
Claims14
A method for predicting one or more sample metric values by machine learning, the method comprising:
- determining a plurality of characteristics from raw data obtained by analysing a proteomics sample in a liquid chromatography mass spectrometer, LC-MS;
- and
- predicting one or more sample metric values by processing the plurality of characteristics using one or more trained machine learning models.
A method of training a machine learning model for predicting a sample metric value, the method comprising:
- determining a plurality of characteristics from raw training data obtained by analysing a training sample in a LC-MS;
- processing the raw training data via a database search to determine the sample metric value for the training sample;
- and
- training the machine learning model using the plurality of characteristics and the sample metric value for the training sample determined via the database search, so that the machine learning model is trained to predict the sample metric value for a subsequent proteomics sample, based on a plurality of characteristics determined from raw data obtained by analysing the subsequent proteomics sample in a LC-MS.
Dependencies are inferred from the claim text.