Constraint-Based Reconstruction and Analysis (COBRA) methods for Genome-wide Metabolic Networks (GEMs) have proven to be essential for the varied applications of metabolic modelling, from predicting growth rate of an organism to production of antibiotics and lethality analysis to name a few. FBA or, Flux Balance Analysis is the earliest COBRA method and the most widely used. But, currently, we have sub-divisions of metabolic modelling strategies which are uncovering the flaws of FBA. To fix these flaws, we have been developing multiple methods which are also being backed by experimental data. So, now we are integrating data from experiments in the models and developing methods for a much better understanding of the metabolic pathways and functionalities of the organisms. The data-driven approaches provide more information about the models and hence provide us with a deeper understanding of the networks.