earticle

영어

There are too many combinatorial gene knock-out targets to achieve the overproduction of desired products. However, researchers cannot perform every single experiment to identify the best combination of gene knock-out targets. This is the reason that computational simulations can play important roles for the overproduction of desired products. Flux balance analysis (FBA) optimizes a specific objective function by linear programming. In order to incorporate the
physiological characteristics of the organisms under gene knock-out conditions, various methods such as MOMA and ROOM were developed. However, these algorithms optimize only the limited objective function. To improve a strain for biochemical production, the organism should be investigated from diverse sides simultaneously. In this respect, we propose a new approach called the flux scanning with compromised objective fluxes (FSCOF) that optimizes
multi-objective functions. [This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MOST) (No. M10309020000-03B5002-00000). Further supports by LG Chem Chair Professorship, Microsoft and IBM SUR program are appreciated.]