Genetic Programming for Gene Regulatory Networks: IRMA Data Analysis

This book discusses the application of Computational Intelligence techniques in biology, particularly in understanding gene regulatory networks and homeostatic regulation. These techniques, such as genetic algorithms and genetic programming, play a crucial role in analyzing gene expression data and inferring regulatory networks. The proposed "A Novel Genetic Programming Approach for Inferring Gene Regulatory Network" algorithm utilizes Polish notation to fit ordinary differential equation models to gene regulatory systems based on time series gene expression data. The algorithm shows promising results in inferring gene regulatory networks in both "Switch ON" and "Switch OFF" conditions. It outperforms existing state-of-the-art methods like BANJO, NIR&TSNI, and GRNGen in terms of precision, sensitivity, and accuracy metrics (F-score). The proposed approach is also applied to infer the gene regulatory network of the GABA signalling family in the Rat Central Nervous System.