Markus J. Herrgård

12.0k total citations · 3 hit papers
84 papers, 7.3k citations indexed

About

Markus J. Herrgård is a scholar working on Molecular Biology, Biomedical Engineering and Genetics. According to data from OpenAlex, Markus J. Herrgård has authored 84 papers receiving a total of 7.3k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Molecular Biology, 26 papers in Biomedical Engineering and 15 papers in Genetics. Recurrent topics in Markus J. Herrgård's work include Microbial Metabolic Engineering and Bioproduction (65 papers), Biofuel production and bioconversion (25 papers) and Gene Regulatory Network Analysis (19 papers). Markus J. Herrgård is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (65 papers), Biofuel production and bioconversion (25 papers) and Gene Regulatory Network Analysis (19 papers). Markus J. Herrgård collaborates with scholars based in Denmark, United States and Sweden. Markus J. Herrgård's co-authors include Bernhard Ø. Palsson, Adam M. Feist, Jennifer L. Reed, Monica L. Mo, Daniel Machado, Markus W. Covert, Ines Thiele, Eric M. Knight, Scott A. Becker and Gregory Hannum and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Markus J. Herrgård

83 papers receiving 7.2k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox

2007 623 citations Adam M. Feist, Bernhard Ø. Palsson et al. profile →
Reconstruction of biochemical networks in microorganisms

2008 621 citations Adam M. Feist, Markus J. Herrgård et al. profile →
Integrating high-throughput and computational data elucidates bacterial networks

2004 592 citations Markus W. Covert, Eric M. Knight et al. Nature profile →

Peers

Markus J. Herrgård

GENET

ECOLO

BIOTE

Christopher S. Henry United States

Radhakrishnan Mahadevan Canada

Vassily Hatzimanikatis Switzerland

Adam M. Feist United States

Sven Panke Switzerland

Kazuyuki Shimizu Japan

Ralf Takors Germany

Maciek R. Antoniewicz United States

Jeffrey D. Orth United States

Kristala L. J. Prather United States

Christopher S. Henry United States

Markus J. Herrgård

5.0k ×0.8

1.7k ×0.7

449 ×0.5

GENET

496 ×1.2

ECOLO

106 ×0.4

BIOTE

Citations per year, relative to Markus J. Herrgård Markus J. Herrgård (= 1×) peers Christopher S. Henry

Countries citing papers authored by Markus J. Herrgård

Since Specialization

Citations

This map shows the geographic impact of Markus J. Herrgård's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Markus J. Herrgård with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus J. Herrgård more than expected).

Fields of papers citing papers by Markus J. Herrgård

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Markus J. Herrgård. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Markus J. Herrgård. The network helps show where Markus J. Herrgård may publish in the future.

Co-authorship network of co-authors of Markus J. Herrgård

This figure shows the co-authorship network connecting the top 25 collaborators of Markus J. Herrgård. A scholar is included among the top collaborators of Markus J. Herrgård based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Markus J. Herrgård. Markus J. Herrgård is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Donati, Stefano, Simo Abdessamad Baallal Jacobsen, Jérôme Maury, et al.. (2023). An automated workflow for multi-omics screening of microbial model organisms. npj Systems Biology and Applications. 9(1). 4 indexed citations

Hartwig, Tanja Schlaikjær, Louise Ambye, Jennifer R. Gruhn, et al.. (2023). Cell-Free Fetal DNA for Genetic Evaluation in Copenhagen Pregnancy Loss Study (COPL): A Prospective Cohort Study. Obstetrical & Gynecological Survey. 78(6). 345–346.

Pedersen, Lasse Ebdrup, Elena Papaleo, Anna Koza, et al.. (2021). A dual-reporter system for investigating and optimizing protein translation and folding in E. coli. Nature Communications. 12(1). 6093–6093. 22 indexed citations

Ögmundarson, Ólafur, Sumesh Sukumara, Markus J. Herrgård, & Peter Fantke. (2020). Combining Environmental and Economic Performance for Bioprocess Optimization. Trends in biotechnology. 38(11). 1203–1214. 70 indexed citations

Pereira, Rui, Elsayed T. Mohamed, Mohammad Radi, et al.. (2020). Elucidating aromatic acid tolerance at low pH in Saccharomyces cerevisiae using adaptive laboratory evolution. Proceedings of the National Academy of Sciences. 117(45). 27954–27961. 62 indexed citations

Mohamed, Elsayed T., Allison Z. Werner, Davinia Salvachúa, et al.. (2020). Adaptive laboratory evolution of Pseudomonas putida KT2440 improves p-coumaric and ferulic acid catabolism and tolerance. Metabolic Engineering Communications. 11. e00143–e00143. 98 indexed citations

Kang, Kang, B. Mikael Bergdahl, Daniel Machado, et al.. (2019). Linking genetic, metabolic, and phenotypic diversity among Saccharomyces cerevisiae strains using multi-omics associations. GigaScience. 8(4). 27 indexed citations

Dahlin, Jonathan, Carina Holkenbrink, Eko Roy Marella, et al.. (2019). Multi-Omics Analysis of Fatty Alcohol Production in Engineered Yeasts Saccharomyces cerevisiae and Yarrowia lipolytica. Frontiers in Genetics. 10. 637738–637738. 34 indexed citations

Luo, Hao, Lei Yang, Konstantin Schneider, et al.. (2019). Coupling S-adenosylmethionine–dependent methylation to growth: Design and uses. PLoS Biology. 17(3). e2007050–e2007050. 45 indexed citations

10.

Massaiu, Ilaria, Lorenzo Pasotti, Nikolaus Sonnenschein, et al.. (2019). Integration of enzymatic data in Bacillus subtilis genome-scale metabolic model improves phenotype predictions and enables in silico design of poly-γ-glutamic acid production strains. Microbial Cell Factories. 18(1). 3–3. 57 indexed citations

11.

McCloskey, Douglas, Julia Xu, Lars Schrübbers, Hanne Bjerre Christensen, & Markus J. Herrgård. (2018). RapidRIP quantifies the intracellular metabolome of 7 industrial strains of E. coli. Metabolic Engineering. 47. 383–392. 24 indexed citations

12.

Kildegaard, Kanchana Rueksomtawin, Niels Bjerg Jensen, Konstantin Schneider, et al.. (2016). Engineering and systems-level analysis of Saccharomyces cerevisiae for production of 3-hydroxypropionic acid via malonyl-CoA reductase-dependent pathway. Microbial Cell Factories. 15(1). 53–53. 96 indexed citations

13.

Monk, Jonathan M., Anna Koza, Miguel A. Campodonico, et al.. (2016). Multi-omics Quantification of Species Variation of Escherichia coli Links Molecular Features with Strain Phenotypes. Cell Systems. 3(3). 238–251.e12. 105 indexed citations

14.

Kildegaard, Kanchana Rueksomtawin, Björn M. Hallström, Thomas Blicher, et al.. (2014). Evolution reveals a glutathione-dependent mechanism of 3-hydroxypropionic acid tolerance. Metabolic Engineering. 26. 57–66. 65 indexed citations

15.

Harrison, Scott J. & Markus J. Herrgård. (2013). The Uses and Future Prospects of Metabolomics and Targeted Metabolite Profiling in Cell Factory Development. Industrial Biotechnology. 9(4). 196–202. 2 indexed citations

16.

Takacs‐Vesbach, Cristina, William P. Inskeep, Zackary J. Jay, et al.. (2013). Metagenome Sequence Analysis of Filamentous Microbial Communities Obtained from Geochemically Distinct Geothermal Channels Reveals Specialization of Three Aquificales Lineages. Frontiers in Microbiology. 4. 84–84. 67 indexed citations

17.

Shlomi, Tomer, Markus J. Herrgård, Vasiliy A. Portnoy, et al.. (2007). Systematic condition-dependent annotation of metabolic genes. Genome Research. 17(11). 1626–1633. 18 indexed citations

18.

Herrgård, Markus J., et al.. (2006). Integrated analysis of regulatory and metabolic networks reveals novel regulatory mechanisms in Saccharomyces cerevisiae. Genome Research. 16(5). 627–635. 165 indexed citations

19.

Covert, Markus W., Eric M. Knight, Jennifer L. Reed, Markus J. Herrgård, & Bernhard Ø. Palsson. (2004). Integrating high-throughput and computational data elucidates bacterial networks. Nature. 429(6987). 92–96. 592 indexed citations breakdown →

20.

Herrgård, Markus J., Markus W. Covert, & Bernhard Ø. Palsson. (2003). Reconstruction of microbial transcriptional regulatory networks. Current Opinion in Biotechnology. 15(1). 70–77. 105 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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