Joshua A. Lerman

Molecular Biology · 2011–2015

A researcher in the Science corpus: 4 papers; trusts 11 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 64 citations into it; #8,283 of 17,773 by trust here, #8,381 by citations
• Biomedical Engineering — 12 citations into it; #10,033 of 10,734 by trust here, #7,854 by citations
• Control and Systems Engineering — 5 citations into it

Whom Joshua A. Lerman trusts overall

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

1. Bernhard O. Palsson
2. Adam M. Feist
3. Jeffrey D. Orth
4. Christopher S. Henry
5. Ines Thiele
6. Nathan E. Lewis
7. Radhakrishnan Mahadevan
8. Kiran Raosaheb Patil
9. Jan Schellenberger
10. C. Schilling

Who trusts Joshua A. Lerman overall

1. Zachary A. King
2. Benjamín J. Sánchez
3. Daniel Machado
4. Ali Ebrahim

Papers from Joshua A. Lerman's perspective

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

1. The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli (Nature Biotechnology)
2. An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR) (Genome Biology)
3. BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models
4. 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)
5. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0 (Nature Protocols)
6. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection (Molecular Systems Biology)
7. A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information (Molecular Systems Biology)
8. The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. (Metabolic Engineering)
9. Towards multidimensional genome annotation (Nature reviews genetics)
10. Thermodynamics-based metabolic flux analysis. (Biophysical Journal)

Their papers

• Genome-scale models of metabolism and gene expression extend and refine growth phenotype prediction (2013) — 495 citations
• BiGG Models: A platform for integrating, standardizing and sharing genome-scale models (2015) — 886 citations
• A comprehensive genome-scale reconstruction of Escherichia coli metabolism—2011 (2011) — 1,090 citations
• COBRApy: COnstraints-Based Reconstruction and Analysis for Python (2013) — 1,250 citations