Mass conservation and inference of metabolic networks from high-throughput mass spectrometry data.
Mass conservation and inference of metabolic networks from high-throughput mass spectrometry data.
复制标题
从高通量质谱数据中进行质量守恒和代谢网络的推断。
DOI：
10.1089/cmb.2010.0222
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Nemenman,Ilya
中科院分区：
文献类型：
--
作者：
Bandaru,Pradeep;Bansal,Mukesh;Nemenman,Ilya
We present a step towards the metabolome-wide computational inference of cellular metabolic reaction networks from metabolic profiling data, such as mass spectrometry. The reconstruction is based on identification of irreducible statistical interactions among the metabolite activities using the ARACNE reverse-engineering algorithm and on constraining possible metabolic transformations to satisfy the conservation of mass. The resulting algorithms are validated on synthetic data from an abridged computational model ofEscherichia colimetabolism. Precision rates upwards of 50% are routinely observed for identification of full metabolic reactions, and recalls upwards of 20% are also seen.
