A flood-based information flow analysis and network minimization method for gene regulatory networks

BMC Bioinformatics

Table 2 Scenarios used in the flood minimization of E. coli regulatory network

Scenario	Inputs	Reporter gene selection	Genes in a sub-network	Reporter genes	Total flood in a network with the flood threshold equals to
					0.00	0.35	0.70
Stationary phase	σ³⁸	Stationary phase specific genes under control of σ³⁸ (22)	1,254	10	185	50	33
Exponential growth / GO groups	σ⁷⁰, σ⁵⁴, σ²⁸	Genes based on GO terms (amino acid synthesis, translation, protein folding, protein modification, glycolysis, tricarboxylic acid cylce)	1,584	168	242	49	48
Exponential growth / expression data	σ⁷⁰, σ⁵⁴, σ²⁸	Genes expressed in the exponential phase (microarray expression data (23)	1,584	54	232	96	40
Heat shock / GO groups	σ³⁸, σ⁵⁴, σ³²	Genes expressed in the exponential phase (microarray expression data (23)	1,314	13	173	46	33
Transition phase / expression data	σ⁷⁰, σ³⁸	Genes expressed in the transition from the exponential to the stationary phase (microarray expression data (23)	1,595	34	241	102	52

Total number of genes is shown for a sub-network regulated by the selected inputs. Total flood is shown for full and minimized networks with three different flood thresholds (the maximum flood through a link is 1.0).

ISSN: 1471-2105