Nathan E. Lewis

Molecular Biology · 2007–2020

A researcher in the Science corpus: 7 papers; trusts 34 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 224 citations into it; #5,743 of 17,773 by trust here, #5,350 by citations
• Biomedical Engineering — 41 citations into it
• Control and Systems Engineering — 8 citations into it
• Genetics — 5 citations into it

Whom Nathan E. Lewis trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Bernhard O. Palsson
2. Jeremy S. Edwards
3. Tomer Shlomi
4. Ramon Grima
5. Ines Thiele
6. Anthony P. Burgard
7. Scott A. Becker
8. Christopher S. Henry
9. Sriram Chandrasekaran
10. Niels Klitgord

Who trusts Nathan E. Lewis overall

1. Ali Ebrahim
2. Edward J. O'Brien
3. Bernhard O. Palsson
4. Koyel Mitra
5. Zachary A. King
6. Ashwin Belle
7. Joshua A. Lerman
8. Jonathan M. Monk
9. Anne-Ruxandra Carvunis
10. Justin Lu

Papers from Nathan E. Lewis's perspective

Ordered by how strongly the researchers Nathan E. Lewis trusts endorse each paper. Same corpus, a different order for every researcher.

1. An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR) (Genome Biology)
2. Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli (Molecular Systems Biology)
3. The Escherichia coli MG1655 in silico metabolic genotype: its definition, characteristics, and capabilities. (Proceedings of the National Academy of Sciences of the United States of America)
4. BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models
5. The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli (Nature Biotechnology)
6. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 (Nature Protocols)
7. Understanding variable importances in forests of randomized trees
8. In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data (Nature Biotechnology)
9. Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. (Genome Research)
10. Towards multidimensional genome annotation (Nature reviews genetics)

Their papers

• Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 (2007) — 1,776 citations
• Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods (2012) — 804 citations
• BiGG Models: A platform for integrating, standardizing and sharing genome-scale models (2015) — 886 citations
• Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways (2015) — 369 citations
• Deciphering cell–cell interactions and communication from gene expression (2020) — 1,074 citations
• MEMOTE for standardized genome-scale metabolic model testing (2020) — 443 citations
• Creation and analysis of biochemical constraint-based models: the COBRA Toolbox v3.0 (2019) — 1,031 citations