Details

Autor(en) / Beteiligte

• Wang, Qingzhao
• Yang, Yudi
• Ma, Hongwu
• Zhao, Xueming

Titel

Metabolic network properties help assign weights to elementary modes to understand physiological flux distributions

Ist Teil von

• Bioinformatics, 2007-05, Vol.23 (9), p.1049-1052

Ort / Verlag

Oxford: Oxford University Press

Erscheinungsjahr

2007

Quelle

MEDLINE

Beschreibungen/Notizen

• Motivation: Elementary modes (EMs) analysis has been well established. The existing methodologies for assigning weights to EMs cannot be directly applied for large-scale metabolic networks, since the tremendous number of modes would make the computation a time-consuming or even an impossible mission. Therefore, developing more efficient methods to deal with large set of EMs is urgent. Result: We develop a method to evaluate the performance of employing a subset of the elementary modes to reconstruct a real flux distribution by using the relative error between the real flux vector and the reconstructed one as an indicator. We have found a power function relationship between the decrease of relative error and the increase of the number of the selecting EMs, and a logarithmic relationship between the increases of the number of non-zero weighted EMs and that of the number of the selecting EMs. Our discoveries show that it is possible to reconstruct a given flux distribution by a selected subset of EMs from a large metabolic network and furthermore, they help us identify the 'governing modes' to represent the cellular metabolism for such a condition. Contact: diana_kingson@yahoo.com.cn(or) Wangqingzhao@eyou.com Supplementary information: Supplementary data are available at Bioinformatics online.