Metabolic network analysis integrated with transcript verification for sequenced genomes.
With sequencing of thousands of organisms completed or in progress, there is a growing need to integrate gene prediction with metabolic network analysis. Using Chlamydomonas reinhardtii as a model, we describe a systems-level methodology bridging metabolic network reconstruction with experimental verification of enzyme encoding open reading frames. Our quantitative and predictive metabolic model and its associated cloned open reading frames provide useful resources for metabolic engineering.
Manichaikul
Ani
A
Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.
Ghamsari
Lila
L
Hom
Erik F Y
EF
Lin
Chenwei
C
Murray
Ryan R
RR
Chang
Roger L
RL
Balaji
S
S
Hao
Tong
T
Shen
Yun
Y
Chavali
Arvind K
AK
Thiele
Ines
I
Yang
Xinping
X
Fan
Changyu
C
Mello
Elizabeth
E
Hill
David E
DE
Vidal
Marc
M
Salehi-Ashtiani
Kourosh
K
Papin
Jason A
JA
D000818:Animals; D016825:Chlamydomonas reinhardtii / Q000201:enzymology / Q000235:genetics / Q000378:metabolism*; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D004798:Enzymes / Q000235:genetics / Q000378:metabolism; D005818:Genetic Engineering; D018503:Genome, Protozoan; D008957:Models, Genetic; D015800:Protozoan Proteins / Q000235:genetics / Q000378:metabolism*; D014158:Transcription, Genetic
D004798:Enzymes; D015800:Protozoan Proteins