Abstract:
:One of the central tasks in systems biology is to understand how cells regulate their metabolism. Hierarchical regulation analysis is a powerful tool to study this regulation at the metabolic, gene-expression, and signaling levels. It has been widely applied to study steady-state regulation, but analysis of the metabolic dynamics remains challenging because it is difficult to measure time-dependent metabolic flux. Here, we develop a nonparametric method that uses Gaussian processes to accurately infer the dynamics of a metabolic pathway based only on metabolite measurements; from this, we then go on to obtain a dynamical view of the hierarchical regulation processes invoked over time to control the activity in a pathway. Our approach allows us to use hierarchical regulation analysis in a dynamic setting but without the need for explicitly time-dependent flux measurements.
journal_name
Biophys Jjournal_title
Biophysical journalauthors
He F,Stumpf MPHdoi
10.1016/j.bpj.2019.04.009subject
Has Abstractpub_date
2019-05-21 00:00:00pages
2035-2046issue
10eissn
0006-3495issn
1542-0086pii
S0006-3495(19)30327-3journal_volume
116pub_type
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