Markus Krummenacker

16.5k total citations · 7 hit papers
41 papers, 9.5k citations indexed

About

Markus Krummenacker is a scholar working on Molecular Biology, Biomedical Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Markus Krummenacker has authored 41 papers receiving a total of 9.5k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 6 papers in Biomedical Engineering and 4 papers in Computational Theory and Mathematics. Recurrent topics in Markus Krummenacker's work include Microbial Metabolic Engineering and Bioproduction (32 papers), Bioinformatics and Genomic Networks (24 papers) and Genomics and Phylogenetic Studies (8 papers). Markus Krummenacker is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (32 papers), Bioinformatics and Genomic Networks (24 papers) and Genomics and Phylogenetic Studies (8 papers). Markus Krummenacker collaborates with scholars based in United States, Mexico and Australia. Markus Krummenacker's co-authors include Peter D. Karp, Suzanne Paley, Ingrid M. Keseler, Mario Latendresse, Ron Caspi, Anamika Kothari, Pallavi Subhraveti, Richard Billington, Carol A. Fulcher and Quang Ong and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Markus Krummenacker

41 papers receiving 9.4k citations

Hit Papers

The MetaCyc database of m... 2007 2026 2013 2019 2015 2007 2013 2019 2017 500 1000 1.5k
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.

  1. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases
    2015 1.9k citations Ron Caspi, Richard Billington et al. Nucleic Acids Research profile →
  2. A genome‐scale metabolic reconstruction for Escherichia coli K‐12 MG1655 that accounts for 1260 ORFs and thermodynamic information
    2007 1.0k citations Adam M. Feist, Christopher S. Henry et al. Molecular Systems Biology profile →
  3. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway/Genome Databases
    2013 867 citations Ron Caspi, Tomer Altman et al. Nucleic Acids Research profile →
  4. The MetaCyc database of metabolic pathways and enzymes - a 2019 update
    2019 795 citations Ron Caspi, Richard Billington et al. Nucleic Acids Research profile →
  5. The MetaCyc database of metabolic pathways and enzymes
    2017 597 citations Ron Caspi, Richard Billington et al. Nucleic Acids Research profile →
  6. The BioCyc collection of microbial genomes and metabolic pathways
    2017 594 citations Peter D. Karp, Richard Billington et al. Briefings in Bioinformatics profile →
  7. Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology
    2009 538 citations Peter D. Karp, Suzanne Paley et al. Briefings in Bioinformatics profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Markus Krummenacker 7.6k 1.5k 1.1k 965 674 41 9.5k
Suzanne Paley 6.8k 0.9× 1.0k 0.7× 1.1k 1.0× 861 0.9× 805 1.2× 60 8.8k
Ingrid M. Keseler 5.9k 0.8× 896 0.6× 1.1k 1.0× 1.0k 1.1× 612 0.9× 28 7.6k
Mario Latendresse 5.3k 0.7× 1.0k 0.7× 951 0.8× 586 0.6× 624 0.9× 46 7.0k
Ron Caspi 5.3k 0.7× 837 0.6× 1.1k 0.9× 665 0.7× 670 1.0× 37 7.3k
Richard Billington 4.9k 0.6× 679 0.5× 825 0.7× 544 0.6× 789 1.2× 88 8.2k
Anamika Kothari 4.4k 0.6× 668 0.5× 835 0.7× 521 0.5× 486 0.7× 16 5.8k
Pallavi Subhraveti 4.3k 0.6× 669 0.5× 841 0.7× 514 0.5× 490 0.7× 12 5.8k
Kiran Raosaheb Patil 6.3k 0.8× 1.5k 1.1× 772 0.7× 503 0.5× 598 0.9× 99 8.1k
Joshua Adkins 7.3k 1.0× 967 0.7× 1.1k 1.0× 1.2k 1.2× 374 0.6× 164 11.0k
Masanori Arita 6.7k 0.9× 864 0.6× 562 0.5× 414 0.4× 1.5k 2.2× 154 9.3k

Countries citing papers authored by Markus Krummenacker

Since Specialization
Citations

This map shows the geographic impact of Markus Krummenacker'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 Krummenacker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Krummenacker more than expected).

Fields of papers citing papers by Markus Krummenacker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Markus Krummenacker. 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 Krummenacker. The network helps show where Markus Krummenacker may publish in the future.

Co-authorship network of co-authors of Markus Krummenacker

This figure shows the co-authorship network connecting the top 25 collaborators of Markus Krummenacker. A scholar is included among the top collaborators of Markus Krummenacker 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 Krummenacker. Markus Krummenacker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Krummenacker, Markus, et al.. (2024). The Genome Explorer genome browser. mSystems. 9(7). e0026724–e0026724. 3 indexed citations
2.
Sun, Gwanggyu, Mialy DeFelice, Taryn E. Gillies, et al.. (2024). Cross-evaluation of E. coli’s operon structures via a whole-cell model suggests alternative cellular benefits for low- versus high-expressing operons. Cell Systems. 15(3). 227–245.e7. 3 indexed citations
3.
Karp, Peter D., Suzanne Paley, Markus Krummenacker, et al.. (2022). Pathway Tools Management of Pathway/Genome Data for Microbial Communities. SHILAP Revista de lepidopterología. 2. 869150–869150. 10 indexed citations
4.
Keseler, Ingrid M., Socorro Gama‐Castro, Amanda Mackie, et al.. (2021). The EcoCyc Database in 2021. Frontiers in Microbiology. 12. 711077–711077. 146 indexed citations
5.
Paley, Suzanne, Ingrid M. Keseler, Markus Krummenacker, & Peter D. Karp. (2021). Leveraging Curation Among Escherichia coli Pathway/Genome Databases Using Ortholog-Based Annotation Propagation. Frontiers in Microbiology. 12. 614355–614355. 4 indexed citations
6.
Krummenacker, Markus, Mario Latendresse, & Peter D. Karp. (2019). Metabolic route computation in organism communities. Microbiome. 7(1). 89–89. 4 indexed citations
7.
Caspi, Ron, Richard Billington, Carol A. Fulcher, et al.. (2017). The MetaCyc database of metabolic pathways and enzymes. Nucleic Acids Research. 46(D1). D633–D639. 597 indexed citations breakdown →
8.
Caspi, Ron, Richard Billington, Luciana Ferrer, et al.. (2015). The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Research. 44(D1). D471–D480. 1906 indexed citations breakdown →
9.
Eker, Steven, Markus Krummenacker, Alexander G. Shearer, et al.. (2013). Computing minimal nutrient sets from metabolic networks via linear constraint solving. BMC Bioinformatics. 14(1). 114–114. 4 indexed citations
10.
Caspi, Rachel R, Tomer Altman, Kate Dreher, et al.. (2011). The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Research. 40(D1). D742–D753. 457 indexed citations
11.
Karp, Peter D., Suzanne Paley, Markus Krummenacker, et al.. (2009). Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology. Briefings in Bioinformatics. 11(1). 40–79. 538 indexed citations breakdown →
12.
Hu, James C., Peter D. Karp, Ingrid M. Keseler, Markus Krummenacker, & Deborah A. Siegele. (2009). What we can learn about Escherichia coli through application of Gene Ontology. Trends in Microbiology. 17(7). 269–278. 8 indexed citations
13.
Keseler, Ingrid M., César Bonavides-Martínez, Julio Collado‐Vides, et al.. (2008). EcoCyc: A comprehensive view of Escherichia coli biology. Nucleic Acids Research. 37(Database). D464–D470. 275 indexed citations
14.
Feist, Adam M., Christopher S. Henry, Jennifer L. Reed, et al.. (2007). A genome‐scale metabolic reconstruction for Escherichia coli K‐12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Molecular Systems Biology. 3(1). 121–121. 1044 indexed citations breakdown →
15.
Karp, Peter D., Ingrid M. Keseler, Alexander G. Shearer, et al.. (2007). Multidimensional annotation of the Escherichia coli K-12 genome. Nucleic Acids Research. 35(22). 7577–7590. 136 indexed citations
16.
Krummenacker, Markus, Suzanne Paley, Lukas A. Mueller, Tingting Yan, & Peter D. Karp. (2005). Querying and computing with BioCyc databases. Computer applications in the biosciences. 21(16). 3454–3455. 51 indexed citations
17.
Karp, Peter D., Markus Krummenacker, Suzanne Paley, & Jonathan Wagg. (1999). Integrated pathway–genome databases and their role in drug discovery. Trends in biotechnology. 17(7). 275–281. 114 indexed citations
18.
Karp, Peter D., et al.. (1999). Eco Cyc: Encyclopedia of Escherichia coli genes and metabolism. Nucleic Acids Research. 27(1). 55–58. 64 indexed citations
19.
Karp, Peter D., et al.. (1997). EcoCyc: Enyclopedia of Escherichia coli Genes and Metabolism. Nucleic Acids Research. 25(1). 43–50. 26 indexed citations
20.
Krummenacker, Markus & James R. Lewis. (1995). Prospects in nanotechnology: toward molecular manufacturing. John Wiley & Sons, Inc. eBooks. 297–297. 14 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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