Integrating large-scale functional genomics data to dissect metabolic networks for hydrogen production

Harwood, Caroline S

关键词: genome sequencing;    bacteria;    hydrogen gas;    bioenergy;    network analysis;   

DOI  :  10.2172/1057459
RP-ID  :  DOE-UW-64688
PID  :  OSTI ID: 1057459

学科分类：再生能源与代替技术

美国|英语

来源: SciTech Connect

【 摘 要 】

The goal of this project is to identify gene networks that are critical for efficient biohydrogen production by leveraging variation in gene content and gene expression in independently isolated Rhodopseudomonas palustris strains. Coexpression methods were applied to large data sets that we have collected to define probabilistic causal gene networks. To our knowledge this a first systems level approach that takes advantage of strain-to strain variability to computationally define networks critical for a particular bacterial phenotypic trait.