Markus J. Herrgård

Molecular Biology · 2004–2020

A researcher in the Science corpus: 9 papers; trusts 18 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 192 citations into it; #1,051 of 17,773 by trust here, #3,296 by citations
• Biomedical Engineering — 28 citations into it; #3,144 of 10,734 by trust here, #6,312 by citations
• Genetics — 15 citations into it

Whom Markus J. Herrgård trusts overall

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

1. Bernhard O. Palsson
2. Radhakrishnan Mahadevan
3. Tomer Shlomi
4. Nathan D. Price
5. Scott A. Becker
6. Douglas B. Kell
7. Adam M. Feist
8. David Weininger
9. C. Schilling
10. Jennie L. Reed

Who trusts Markus J. Herrgård overall

1. Bernhard O. Palsson
2. Karthik Raman
3. Jan Schellenberger
4. Matthew A. Oberhardt
5. Sriram Chandrasekaran
6. Nathan D. Price
7. Rasmus Agren
8. Niels Klitgord
9. Guy Karlebach
10. Nagasuma R. Chandra

Papers from Markus J. Herrgård's perspective

Ordered by how strongly the researchers Markus J. Herrgård 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. BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models
3. Genome-scale microbial in silico models: the constraints-based approach. (Trends in Biotechnology)
4. KEGG: Kyoto Encyclopedia of Genes and Genomes (Nucleic Acids Res.)
5. From genomics to chemical genomics: new developments in KEGG (Nucleic Acids Res.)
6. HMDB: the Human Metabolome Database (Nucleic Acids Res.)
7. Gene Ontology: tool for the unification of biology
8. Metabolic gene–deletion strains of Escherichia coli evolve to computationally predicted growth phenotypes (Nature Genetics)
9. Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli (Molecular Systems Biology)
10. Controlling the false discovery rate: a practical and powerful approach to multiple testing

Their papers

• Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox (2007) — 874 citations
• Integrating high-throughput and computational data elucidates bacterial networks (2004) — 845 citations
• Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. (2004) — 699 citations
• Network-based prediction of human tissue-specific metabolism (2008) — 681 citations
• Reconstruction of Biochemical Networks in Microbial Organisms (2008) — 876 citations
• Pharmacogenomic and clinical data link non-pharmacokinetic metabolic dysregulation to drug side effect pathogenesis (2015) — 46 citations
• A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology (2008) — 617 citations
• Systematic Evaluation of Methods for Integration of Transcriptomic Data into Constraint-Based Models of Metabolism (2014) — 406 citations
• MEMOTE for standardized genome-scale metabolic model testing (2020) — 443 citations