Edward J. O'Brien
Molecular Biology · with Palsson · 2013–2015
A researcher in the Science corpus: 2 papers; trusts 15 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Molecular Biology — 53 citations into it; #9,844 of 17,773 by trust here, #11,207 by citations
- Biomedical Engineering — 15 citations into it; #7,835 of 10,734 by trust here, #8,044 by citations
- Genetics — 10 citations into it
Whom Edward J. O'Brien trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Bernhard O. Palsson
- Ines Thiele
- Jennie L. Reed
- Scott A. Becker
- Christopher S. Henry
- Nathan E. Lewis
- Matthew A. Oberhardt
- Adam M. Feist
- Markus W. Covert
- Tomer Shlomi
Who trusts Edward J. O'Brien overall
- James C. Liao
- Benjamín J. Sánchez
- R. Jacoby
- Cheng Zhang
- Michael Ku Yu
- Avlant Nilsson
- Manuela Peukert
Papers from Edward J. O'Brien's perspective
Ordered by how strongly the researchers Edward J. O'Brien trusts endorse each paper. Same corpus, a different order for every researcher.
- Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox (Nature Protocols)
- The challenges of in silico biology (Nature Biotechnology)
- Thermodynamics-based metabolic flux analysis. (Biophysical Journal)
- Network-based prediction of human tissue-specific metabolism (Nature Biotechnology)
- Integrating high-throughput and computational data elucidates bacterial networks (Nature)
- Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods (Nature Reviews Microbiology)
- Global reconstruction of the human metabolic network based on genomic and bibliomic data (Proceedings of the National Academy of Sciences of the United States of America)
- Applications of genome-scale metabolic reconstructions (Molecular Systems Biology)
- Constraint-based models predict metabolic and associated cellular functions (Nature reviews genetics)
- Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli (Molecular Systems Biology)
Their papers
- Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction (2013) — 495 citations
- Using Genome-Scale Models to Predict Biological Capabilities (2015) — 684 citations