Student Publications

Export 21 results:
Filters: Keyword is Phenotype  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
Famili I, Forster J, Nielsen J, Palsson BO. "Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network." Proc. Natl. Acad. Sci. U.S.A.. 2003;100(23):13134-9.
Fong SS, Joyce AR, Palsson BØ. "Parallel adaptive evolution cultures of Escherichia coli lead to convergent growth phenotypes with different gene expression states." Genome Res.. 2005;15(10):1365-72.
Förster J, Famili I, Fu P, Palsson BØ, Nielsen J. "Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network." Genome Res.. 2003;13(2):244-53.
Haugen AC, Kelley R, Collins JB, et al. "Integrating phenotypic and expression profiles to map arsenic-response networks." Genome Biol.. 2004;5(12):R95.
Herrgård MJ, Fong SS, Palsson BØ. "Identification of genome-scale metabolic network models using experimentally measured flux profiles." PLoS Comput. Biol.. 2006;2(7):e72.
Kang H M, Zaitlen NA, Wade CM, et al. "Efficient control of population structure in model organism association mapping." Genetics. 2008;178(3):1709-23.
Lee TK, Denny EM, Sanghvi JC, et al. "A noisy paracrine signal determines the cellular NF-kappaB response to lipopolysaccharide." Sci Signal. 2009;2(93):ra65.
Lerman J, Palsson BO. "Microbiology. Topping off a multiscale balancing act." Science. 2010;330(6007):1058-9.
Lewis NE, Nagarajan H, Palsson BO. "Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods." Nat. Rev. Microbiol.. 2012;10(4):291-305.
Lewis NE, Hixson KK, Conrad TM, et al. "Omic data from evolved E. coli are consistent with computed optimal growth from genome-scale models." Mol. Syst. Biol.. 2010;6:390.
Liu G-H, Barkho BZ, Ruiz S, et al. "Recapitulation of premature ageing with iPSCs from Hutchinson-Gilford progeria syndrome." Nature. 2011;472(7342):221-5.
Suthram S, Beyer A, Karp RM, Eldar Y, Ideker T. "eQED: an efficient method for interpreting eQTL associations using protein networks." Mol. Syst. Biol.. 2008;4:162.