New Informatics Approach Combines Metabolic, Regulatory Networks to Elucidate Cells' Activities
A new paper written by researchers from the Institute for Systems Biology describes a computational approach for studying regulatory activities in cells that relies on integrated networks of transcriptional and metabolic data. The study, published in PLOS Computational Biology earlier this month, describes software called the Gene Expression and Metabolism Integrated for Network Inference (GEMINI) which uses an integrated model of network and metabolic data to explore growth phenotypes in Saccharomyces cerevisiae . GEMINI builds on work from the same researchers published in 2010 in the Proceedings of the National Academy of Sciences . That paper describes the Probabilistic Regulation of Metabolism (PROM), which provides a mechanism for integrating transcriptional regulatory networks and metabolic networks in a single in silico model and using it to make predictions about phenotypes such as flux and growth rate. While based on PROM, GEMINI is designed to tackle a slightly dif...