Abstract: A computer implemented method for analyzing host phage response data comprises fitting a sequence of sigmoidal functions at each time point from a start time to an end time and selecting the best fit at each point. The best fit over all the time points is then selected, and a search performed for a time point with a similar coefficient of determination, but closer in time to a minimum time point indicative of the end of the lag phase. The lag time for the best fit time point is then obtained from the fitted model. If the best fit fails a threshold test then the dataset is considered to be flat and the lag time is set to the end time.

Abstract: A computer implemented method of generating a machine learning model for interpreting host phage response data comprising receiving datasets and labels for a host phage response, training a machine learning model and using this model to estimate the efficacy of a test phage in inhibiting growth of a test bacteria.

Abstract: The present invention concerns a method for discovering at least a biomarkers signature from biomarker data pools, the method comprising the steps of: i) Generating a set of signatures (1, 2) with fuzzy logic and evolutionary algorithms, each signature reciting a determined number of biomarkers; ii) Selecting at least a target signature from said set of signatures by applying at least the following filters on said set of signatures (1, 2): a) a performance filter; b) a frequency filter; and c) a dominance filter. The present invention further relates to device for discovering at least a biomarkers signature from biomarker data pools and to a use of a biomarker signature discovered by a method according to the present invention for diagnosing, predicting or monitoring a disease.