Tool name | Ref. | Visualization | Run | Oper. mode | Model handling |
---|
| | Supervised | Unsupervised | User-supplied | FBA | FVA | MOMA | Gene/rxn | Stand-alone | Web-based | Build | Edit | Import SBML | Export SBML |
---|
FAME | | ● | | ● | ● | ● | | ● | | ● | ● | ● | ● | ● |
Model SEED | [2] | ● | | | ● | | | ○1 | | ● | ● | ○2 | | ● |
COBRA Toolbox | [3] | | | ● | ● | ● | ● | ● | | | ● | ● | ○3 | ○3 |
OptFlux | [4] | | | ● | ● | ● | ● | ● | ● | | | | ● | ● |
CellNetAnalyzer | [5] | | | ● | ● | ● | | | | | | | ● | ● |
PySCeS | [7] | | | | ● | ● | | | ○4 | | | ● | ● | ● |
YANASquare | [13] | | ● | ● | ● | | | | ● | | ● | ● | ● | |
MEGU | [14] | ● | | | | | | | | ● | | | | |
BioMet Toolbox | [15] | | | | ● | | | ● | ○4 | ● | | | | |
Cytoscape | [16] | | ● | ● | | | | ○1 | ● | | ● | ● | | |
-
Notes:
- 1. Gene/reaction associations are used to build models, but no analyses are performed on them.
- 2. Model SEED has only limited editing capabilities once a model has been produced.
- 3. The COBRA Toolbox uses an SBML dialect specific to this tool.
- 4. Certain dependencies must be installed first.
- A comparison of the features offered in FAME and existing alternatives. A ● indicates a feature that is present; an open circle (○) denotes a partial implementation of the feature in question. Under visualization, "supervised" means the application uses predefined network topologies, "unsupervised" means networks are drawn on the fly, as graphs, and "user-supplied" means that visualization is performed on user-supplied network topology maps.
- Under "Run", MOMA represents Minimization Of Metabolic Adjustments, which is described in [17]. Most packages feature additional analyses besides the ones listed in this table. As many of these tools are custom-built for these analyses, or vice versa, we do not list those analysis options in this table. The tools whose functionalities most resemble FAME's have no web interface or have inferior visualization capabilities. On the other hand, tools featuring (or focusing on) superior visualization lack the powerful analysis features unlocked by PySCeS-CBM.