There are 16 Different Combinations for the Test Inputs

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Presentation transcript:

There are 16 Different Combinations for the Test Inputs Sigmoidal Estimate + Forward Estimate b, Estimate p Graph No Graph Estimate b, Fix p Fix b, Estimate p Fix b, Fix p Forward Only Michaelis Menten Fix p Estimate p

There was little difference in the values of the Network Optimized Weights for Graph and No Graph Difference Between Graph and No Graph Sigmoidal: Estimate and Forward Fixb-0 and FixP-0 9.5E-18 Fixb-0 and FixP-1 -3.5E-08 Fixb-1 and FixP-0 Fixb-1 and FixP-1 Sigmoidal: Forward only Michaelis Menten: Estimate and Forward FixP-1 8.8E-08 FixP-0 -9.0E-08 Michaelis Menten: Forward only

ControllerGeneA -> TargetGeneB Network Optimized Weights for Sigmoidal and Michaelis Menten Estimate + Forward ControllerGeneA -> TargetGeneB

ACE2

ARG80

CIN5

FKH2

GLN3

HAP4

HMO1 Note that the scale is from -6 to 6, rather than -3 to 3

MIG2 Note that the scale is from -6 to 6, rather than -3 to 3

MSN2 Note that the scale is from -6 to 6, rather than -3 to 3

PDR1

PIB2

RIF1

SFP1

SNF6

STB5

SWI4

SWI5

YHP1

YLR278C

YOX1

Network b Output Comparison for Sigmoidal Model

There is an Issue with the Production Rates for Estimating P (fixP-0)

Input GRNsight

Sigmoidal_estimation_fixb-0_fixP-0_graph_output GRNsight

Sigmoidal_estimation_fixb-0_fixP-1_graph GRNsight

Sigmoidal_estimation_fixb-1_fixP-0_graph GRNsight

Sigmoid_estimation_fixb-1_fixP-1_graph GRNsight

Sigmoid_forward_graph GRNsight

MM_estimation_fixP-1_graph GRNsight

MM_estimation_fixP-0_graph GRNsight

MM_forward_graph GRNsight