Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme

• Published in: BMC genomics Vol. 18; no. Suppl 2; p. 209
• Main Authors: Li, Dong, Pan, Zhisong, Hu, Guyu, Zhu, Zexuan, He, Shan
• Format: Journal Article
• Language: English
• Published: London BioMed Central 14.03.2017; Springer Nature B.V
• Subjects: Accuracy; Acids; Agglomeration; Algorithms; Animal Genetics and Genomics; Bioinformatics; Biological effects; Biological properties; Biology; Biomedical and Life Sciences; CCR6 protein; CD4 antigen; Cell cycle; Combinatorial analysis; Community structure; Computer applications; Computer networks; Computer programs; Decoding; Differentiation; DNA microarrays; Encoding-Decoding; Gene expression; Gene Regulatory Networks; Genetic algorithms; Genomes; Genomics; Helper cells; Heuristic methods; Humans; Identification; Identification methods; Integration; Interleukin 17; Interleukin 21; Life Sciences; Literature reviews; Lymphocytes T; Mathematical models; Metabolic response; Metabolism; Microarrays; Microbial Genetics and Genomics; Modules; Mutation; Nodes; Operators; Operators (mathematics); Optimization; Optimization algorithms; Pertussis; Plant Genetics and Genomics; Probability theory; Problem solving; Protein Interaction Mapping - statistics & numerical data; Protein Interaction Maps; Proteins; Proteomics; Signal Transduction; Simulated annealing; Simulation; Transcription; Vaccines; Memetic algorithm; Connectedness; Module identification; Module size
• ISSN: 1471-2164; 1471-2164
• DOI: 10.1186/s12864-017-3495-y

Background Active modules are connected regions in biological network which show significant changes in expression over particular conditions. The identification of such modules is important since it may reveal the regulatory and signaling mechanisms that associate with a given cellular response. Results In this paper, we propose a novel active module identification algorithm based on a memetic algorithm. We propose a novel encoding/decoding scheme to ensure the connectedness of the identified active modules. Based on the scheme, we also design and incorporate a local search operator into the memetic algorithm to improve its performance. Conclusion The effectiveness of proposed algorithm is validated on both small and large protein interaction networks.