Journal of integrative bioinformatics

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The official bioinformatics tool list for the Journal of Integrative Bioinformatics (JIB).

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Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS) statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs), protein-protein interactions (PPIs) and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs) approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

JIB Publications
  • Liu L, Mei Q, Yu Z, Sun T, Zhang Z, Chen M. An integrative bioinformatics framework for genome-scale multiple level network reconstruction of rice. J Integr Bioinform. 2013;10(2):223. doi 10.2390/biecoll-jib-2013-223; PubMed 23563093