Multiplex methods provide effective integration of multi-omic data in genome-scale models

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• 作者：Claudio Angione ; Max Conway ; Pietro Lió
• 关键词：Genome ; scale models ; Multiplex networks ; Multi ; omics ; Network fusion ; Transcriptomics ; Fluxomics ; Flux balance analysis
• 刊名：BMC Bioinformatics
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：17
• 期：4-supp
• 全文大小：1,909 KB
• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Combinatorial Libraries; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105

文摘

Background Genomic, transcriptomic, and metabolic variations shape the complex adaptation landscape of bacteria to varying environmental conditions. Elucidating the genotype-phenotype relation paves the way for the prediction of such effects, but methods for characterizing the relationship between multiple environmental factors are still lacking. Here, we tackle the problem of extracting network-level information from collections of environmental conditions, by integrating the multiple omic levels at which the bacterial response is measured.