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126 Investigations visible to you, out of a total of 324
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This is a collection of deep eutectic solvent (DES) experimental and simulation data that is stored in CML format and analysed using gradient boosting decision trees.

Publication data made available for Biotechnology Reports, supplementary data

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Supplementary files for the publication:
Deep Neural Networks Outperform Human Expert’s Capacity in Characterizing Bioleaching Bacterial Biofilm Composition

Gene co-epxression network analyses are common in the study of large scale biological data sets. In this study, we have developed a methodology for the comparison of pairs of co-expression networks using the s-core network peeling approach. We apply the methodology to gene-expression data for human and mouse.

Aim. Constructing a predictive, dynamic model of the redox metabolism of trypanosomes. Aided by
this model we will quantify the impact of gene-expression and metabolic regulation on redox
metabolism. The model will be constructed in an iterative cycle of experimentation – modelling –
analysis – experimentation, such that it can be extended and refined based on new experimental

Changing the oxygen availability leads to an adaptation of Escherichia coli at different biological levels. After pertubation of oxygen in chemostat experiments there are very quick responses. This investigation deals with this dynamical behaviour (transitions) of Escherichia coli within the aerobiosis scale. The change for different biological variables, in different areas of the organism like the electron transport chain, the TCA cycle or globally is investigated by wildtype and mutants experiments

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