Mass Conservation And Inference of Metabolic Networks from High-throughput Mass Spectrometry Data

Details 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

2010-07-06

arxiv.org/abs/1007.0986v1

J Comput Biol, vol. 18 (2) pp. 147-54, 2011

Biology

Quantitative Biology

Quantitative Methods

18 pages

Scientific paper

10.1089/cmb.2010.0222

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 of Escherichia coli metabolism. Precision rates upwards of 50% are routinely observed for identification of full metabolic reactions, and recalls upwards of 20% are also seen.

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