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A Dimension Reduction Method for Inferring Biochemical Networks | | Gheorghe Craciun
; Casian Pantea
; Grzegorz A. Rempala
; | | Date: |
25 Feb 2009 | | Abstract: | We present herein an extension of an algebraic statistical method for
inferring biochemical reaction networks from experimental data, proposed
recently in [3]. This extension allows us to analyze reaction networks that are
not necessarily full-dimensional, i.e., the dimension of their stoichiometric
space is smaller than the number of species. Specifically, we propose to
augment the original algebraic-statistical algorithm for network inference with
a preprocessing step that identifies the subspace spanned by the correct
reaction vectors, within the space spanned by the species. This dimension
reduction step is based on principal component analysis of the input data and
its relationship with various subspaces generated by sets of candidate reaction
vectors. Simulated examples are provided to illustrate the main ideas involved
in implementing this method, and to asses its performance. | | Source: | arXiv, 0902.4417 | | Services: | Forum | Review | PDF | Favorites | |
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