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原文連結
論文資訊
- 類型：已發表論文
- 日期：2009
摘要
Background: Reverse engineering of gene regulatory 網絡s presents one of the big challenges in systems biology. Gene regulatory 網絡s are usually inferred from a set of single-gene over- expressions and/or knockout experiments. Functional relationships between genes are retrieved either from the steady state gene expressions or from respective time series. Results: We present a novel algorithm for gene 網絡 reconstruction on the basis of steady-state gene-chip data from over-expression experiments. The algorithm is based on a straight forward solution of a linear gene-dynamics equation, where experimental data is fed in as a first predictor for the solution. We compare the algorithm's performance with the NIR algorithm, both on the well known E. coli experimental data and on in-silico experiment
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