Year |
Citation |
Score |
2016 |
Auslander N, Wagner A, Oberhardt M, Ruppin E. Data-Driven Metabolic Pathway Compositions Enhance Cancer Survival Prediction. Plos Computational Biology. 12: e1005125. PMID 27673682 DOI: 10.1371/Journal.Pcbi.1005125 |
0.365 |
|
2016 |
Shaked I, Oberhardt MA, Atias N, Sharan R, Ruppin E. Metabolic Network Prediction of Drug Side Effects. Cell Systems. 2: 209-13. PMID 27135366 DOI: 10.1016/J.Cels.2016.03.001 |
0.372 |
|
2016 |
Oberhardt MA, Zarecki R, Reshef L, Xia F, Duran-Frigola M, Schreiber R, Henry CS, Ben-Tal N, Dwyer DJ, Gophna U, Ruppin E. Systems-Wide Prediction of Enzyme Promiscuity Reveals a New Underground Alternative Route for Pyridoxal 5'-Phosphate Production in E. coli. Plos Computational Biology. 12: e1004705. PMID 26821166 DOI: 10.1371/Journal.Pcbi.1004705 |
0.384 |
|
2014 |
Oberhardt MA, Gianchandani EP. Genome-scale modeling and human disease: an overview. Frontiers in Physiology. 5: 527. PMID 25667572 DOI: 10.3389/Fphys.2014.00527 |
0.71 |
|
2014 |
Eilam O, Zarecki R, Oberhardt M, Ursell LK, Kupiec M, Knight R, Gophna U, Ruppin E. Glycan degradation (GlyDeR) analysis predicts mammalian gut microbiota abundance and host diet-specific adaptations. Mbio. 5. PMID 25118239 DOI: 10.1128/Mbio.01526-14 |
0.353 |
|
2014 |
Zarecki R, Oberhardt MA, Reshef L, Gophna U, Ruppin E. A novel nutritional predictor links microbial fastidiousness with lowered ubiquity, growth rate, and cooperativeness. Plos Computational Biology. 10: e1003726. PMID 25033033 DOI: 10.1371/Journal.Pcbi.1003726 |
0.393 |
|
2014 |
Zarecki R, Oberhardt MA, Yizhak K, Wagner A, Shtifman Segal E, Freilich S, Henry CS, Gophna U, Ruppin E. Maximal sum of metabolic exchange fluxes outperforms biomass yield as a predictor of growth rate of microorganisms. Plos One. 9: e98372. PMID 24866123 DOI: 10.1371/Journal.Pone.0098372 |
0.38 |
|
2013 |
Oberhardt MA, Yizhak K, Ruppin E. Metabolically re-modeling the drug pipeline. Current Opinion in Pharmacology. 13: 778-85. PMID 23731523 DOI: 10.1016/J.Coph.2013.05.006 |
0.333 |
|
2011 |
Oberhardt MA, Pucha?ka J, Martins dos Santos VA, Papin JA. Reconciliation of genome-scale metabolic reconstructions for comparative systems analysis. Plos Computational Biology. 7: e1001116. PMID 21483480 DOI: 10.1371/Journal.Pcbi.1001116 |
0.635 |
|
2011 |
Benedict KF, Mac Gabhann F, Amanfu RK, Chavali AK, Gianchandani EP, Glaw LS, Oberhardt MA, Thorne BC, Yang JH, Papin JA, Peirce SM, Saucerman JJ, Skalak TC. Systems analysis of small signaling modules relevant to eight human diseases. Annals of Biomedical Engineering. 39: 621-35. PMID 21132372 DOI: 10.1007/S10439-010-0208-Y |
0.612 |
|
2010 |
Oberhardt MA, Goldberg JB, Hogardt M, Papin JA. Metabolic network analysis of Pseudomonas aeruginosa during chronic cystic fibrosis lung infection. Journal of Bacteriology. 192: 5534-48. PMID 20709898 DOI: 10.1128/Jb.00900-10 |
0.613 |
|
2009 |
Oberhardt MA, Palsson BØ, Papin JA. Applications of genome-scale metabolic reconstructions. Molecular Systems Biology. 5: 320. PMID 19888215 DOI: 10.1038/Msb.2009.77 |
0.663 |
|
2009 |
Oberhardt MA, Chavali AK, Papin JA. Flux balance analysis: interrogating genome-scale metabolic networks. Methods in Molecular Biology (Clifton, N.J.). 500: 61-80. PMID 19399432 DOI: 10.1007/978-1-59745-525-1_3 |
0.72 |
|
2008 |
Pucha?ka J, Oberhardt MA, Godinho M, Bielecka A, Regenhardt D, Timmis KN, Papin JA, Martins dos Santos VA. Genome-scale reconstruction and analysis of the Pseudomonas putida KT2440 metabolic network facilitates applications in biotechnology. Plos Computational Biology. 4: e1000210. PMID 18974823 DOI: 10.1371/Journal.Pcbi.1000210 |
0.658 |
|
2008 |
Gianchandani EP, Oberhardt MA, Burgard AP, Maranas CD, Papin JA. Predicting biological system objectives de novo from internal state measurements. Bmc Bioinformatics. 9: 43. PMID 18218092 DOI: 10.1186/1471-2105-9-43 |
0.716 |
|
2008 |
Oberhardt MA, Pucha?ka J, Fryer KE, Martins dos Santos VA, Papin JA. Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1. Journal of Bacteriology. 190: 2790-803. PMID 18192387 DOI: 10.1128/Jb.01583-07 |
0.659 |
|
2007 |
Robertson SH, Smith CK, Langhans AL, McLinden SE, Oberhardt MA, Jakab KR, Dzamba B, DeSimone DW, Papin JA, Peirce SM. Multiscale computational analysis of Xenopus laevis morphogenesis reveals key insights of systems-level behavior. Bmc Systems Biology. 1: 46. PMID 17953751 DOI: 10.1186/1752-0509-1-46 |
0.549 |
|
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