Comment of Global dynamics of biological systems

TL;DR

This paper critically examines claims about using nonlinear time series analysis and SSA to understand the global dynamics of gene expression in biological systems, raising concerns about their applicability and validity.

Contribution

It provides a systematic critique of the use of SSA and nonlinear analysis methods in inferring biological system dynamics, highlighting potential limitations.

Findings

Questions the validity of SSA for biological time series analysis

Highlights potential misinterpretations of eigen-spectrum flattening

Warns against overreliance on nonlinear time series methods in biology

Abstract

In a recent study, (Grigorov, 2006) analyzed temporal gene expression profiles (Arbeitman et al., 2002) generated in a Drosophila experiment using SSA in conjunction with Monte-Carlo SSA. The author (Grigorov, 2006) makes three important claims in his article, namely: Claim1: A new method based on the theory of nonlinear time series analysis is used to capture the global dynamics of the fruit-fly cycle temporal gene expression profiles. Claim 2: Flattening of a significant part of the eigen-spectrum confirms the hypothesis about an underly-ing high-dimensional chaotic generating process. Claim 3: Monte-Carlo SSA can be used to establish whether a given time series is distinguishable from any well-defined process including deterministic chaos. In this report we present fundamental concerns with respect to the above claims (Grigorov, 2006) in a systematic manner with simple examples. The discussion provided especially discourages the choice of SSA for inferring nonlinear dynamical structure form time series obtained in any biological paradigm.