Abstract Transfer of laboratory-scale experiments to production-scale ethanol fermentation is time-consuming and involves expensive prototype systems from complex experimental designs that determine optimal operating conditions for minimal substrate and product inhibitions.The study developed and validated a Simulink-based model for optimal pH and
A feature selection strategy for gene expression time series experiments with hidden Markov models.
Studies conducted in time series could be far more informative than those that only capture a specific moment in time.However, when it comes to transcriptomic data, time points are sparse creating the need for a constant search for methods capable of extracting information out of experiments of this kind.We propose a feature selection algorithm emb