Skip to main content

Table 2 Predictive accuracy through the comparison of predicted fluxes and measured fluxes in eight conditions (DataE1) for both the DC and AC models

From: ICON-GEMs: integration of co-expression network in genome-scale metabolic models, shedding light through systems biology

Conditions

Predictive accuracy

DC model

AC model

E-flux

E-flux2

ICON-GEMs

E-flux

E-flux2

ICON-GEMs

WT 0.2 per hour

0.8221

0.8852

0.9443

0.3893

0.6293

0.5619

\(pgm\)

0.8486

0.8672

0.9639

0.6676

0.6389

0.6804

\(pgi\)

0.8674

0.8237

0.9107

0.4990

0.6129

0.3971

\(gapC\)

0.6564

0.8546

0.8828

0.5019

0.7012

0.4649

\(zwf\)

0.8110

0.8538

0.8731

0.3290

0.6499

0.5373

\(rpe\)

0.8947

0.8885

0.8733

0.3683

0.6221

0.7078

WT 0.5 per hour

0.8094

0.9031

0.9656

0.5629

0.6615

0.7715

WT 0.7 per hour

0.8687

0.8699

0.8962

0.6711

0.6870

0.7424

Mean

0.8223

0.8682

0.9206

0.1225

0.6504

0.6079

Standard Deviation

0.0688

0.0231

0.0333

0.1555

0.0292

0.1284

  1. The bold numbers indicate the highest predictive accuracy values for each condition
  2. Eight distinct conditions encompass wild-type E. coli growth rates at 0.2 (as reference (RF)), 0.5 (WT0.5), and 0.7 (WT0.7) per hour as well as specific gene deletions (of genes pgm, pgi, gapc, zwf, and rpe)
Back to article page

BMC Bioinformatics

ISSN: 1471-2105

Contact us