D. McCloskey

Molecular Biology · 2013–2019

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 59 citations into it
• Biomedical Engineering — 14 citations into it
• Genetics — 11 citations into it

Whom D. McCloskey trusts overall

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

1. Bernhard O. Palsson
2. Adam M. Feist
3. Christopher S. Henry
4. Jeremy S. Edwards
5. K. Datsenko
6. Jeffrey D. Orth
7. Tomer Shlomi
8. Avi I. Flamholz
9. Markus W. Covert
10. Jennie L. Reed

Who trusts D. McCloskey overall

1. Daniel Machado

Papers from D. McCloskey's perspective

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

1. Genome-scale models of microbial cells: evaluating the consequences of constraints (Nature Reviews Microbiology)
2. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection (Molecular Systems Biology)
3. A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information (Molecular Systems Biology)
4. Thermodynamics-based metabolic flux analysis. (Biophysical Journal)
5. One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products. (Proceedings of the National Academy of Sciences of the United States of America)
6. The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli (Nature Biotechnology)
7. 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)
8. Global organization of metabolic fluxes in the bacterium Escherichia coli (Nature)
9. Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli (Molecular Systems Biology)
10. Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth (Nature)

Their papers

• Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli (2013) — 359 citations
• A white-box machine learning approach for revealing antibiotic mechanisms of action (2019) — 285 citations