Resolution:
## Figure 4.
State space modeling predicts transcription factor influence. (a) Conceptual scheme of the state space modeling. An unknown function f (red square)
relates the values of latent variables Z(t) and Z(t + 1) (for all t) corresponding
to consecutive time measurements. Learning algorithms iteratively optimize the function
f mapping latent values of transcription factors to changes to target genes (and transcription
factors themselves at time t + 1). (b) The whole dataset (from 0 to 20 minutes of KNO_{3 }treatment) has been learnt by state space modeling (validated to be predictive in
a leave-one-last approach; Table 2). The resulting f function has learnt possible connections and can be displayed as an influence matrix.
SPL9 is a transcription factor predicted to be a potential bottleneck and is further
experimentally studied.
Krouk |