000202702 001__ 202702
000202702 005__ 20190317000035.0
000202702 037__ $$aPOST_TALK
000202702 245__ $$aUnlocking Yeast Metabolism: Identification of optimal flux directionalities
000202702 269__ $$a2013
000202702 260__ $$c2013
000202702 336__ $$aTalks
000202702 520__ $$aMetabolic modeling has proven to be a valuable tool in the investigation of cellular physiology, especially in the post-genomic era. However, the sheer complexity of even the simplest metabolic networks obstructs the exact determination of intracellular states, despite the ample supply of –omics data. To overcome this difficulty we attempt to postulate simplifying assumptions, relevant to the conditions and available data. Identifying the gamut of possible feasible states allows us to query for factors that are crucial in interpreting the observed physiology or in developing metabolic engineering strategies. Towards this end, we developed a framework called Flux Directionality Profile Analysis (FDPA) that enables both the complete enumeration and the characterization of all possible intracellular flux states. The proposed methodology allows for the seamless incorporation of available experimental data, when available, such as reaction fluxes, uptake rates, intra- and extra-cellular metabolite concentration measurements and splitting ratios at metabolic branching points. Additionally, FDPA employs a set of speculative metabolic objectives in order to rank the thermodynamically feasible intracellular flux states based on their performance against one (or more) of these objectives. We are therefore able to isolate internal flux states that are both thermodynamically consistent and relevant to the observed physiology.
000202702 6531_ $$athermodynamics
000202702 6531_ $$aflux balance analysis
000202702 6531_ $$aMonte-Carlo Hit-and-Run sampling
000202702 6531_ $$anetwork analysis
000202702 6531_ $$ametabolomics
000202702 700__ $$0246757$$g229920$$aKiparissides, Alexandros
000202702 700__ $$0240448$$g133818$$aSoh, Keng Cher
000202702 700__ $$0240657$$g174688$$aChakrabarti, Anirikh
000202702 700__ $$aMiskovic, Ljubisa$$g133818$$0240448
000202702 700__ $$aHatzimanikatis, Vassily$$g174688$$0240657
000202702 7112_ $$dNovember 3-8, 2013$$cSan Francisco, CA, USA$$a2013 AIChE Annual Meeting
000202702 8564_ $$uhttps://infoscience.epfl.ch/record/202702/files/Kiparissides_AiCHE_2013_336186_766a_Final.pptx$$zn/a$$s20814549$$yn/a
000202702 909C0 $$xU11422$$0252131$$pLCSB
000202702 909CO $$ooai:infoscience.tind.io:202702$$qGLOBAL_SET$$ppresentation$$pSB
000202702 917Z8 $$x229920
000202702 917Z8 $$x133818
000202702 917Z8 $$x133818
000202702 937__ $$aEPFL-TALK-202702
000202702 973__ $$aEPFL
000202702 980__ $$aTALK