Karoline Faust

22.7k total citations · 6 hit papers
65 papers, 8.3k citations indexed

About

Karoline Faust is a scholar working on Molecular Biology, Ecology and Biomedical Engineering. According to data from OpenAlex, Karoline Faust has authored 65 papers receiving a total of 8.3k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Molecular Biology, 25 papers in Ecology and 10 papers in Biomedical Engineering. Recurrent topics in Karoline Faust's work include Gut microbiota and health (33 papers), Microbial Community Ecology and Physiology (23 papers) and Bioinformatics and Genomic Networks (20 papers). Karoline Faust is often cited by papers focused on Gut microbiota and health (33 papers), Microbial Community Ecology and Physiology (23 papers) and Bioinformatics and Genomic Networks (20 papers). Karoline Faust collaborates with scholars based in Belgium, United States and China. Karoline Faust's co-authors include Jeroen Raes, Lisa Röttjers, J. Fah Sathirapongsasuti, Curtis Huttenhower, Nicola Segata, Dirk Gevers, Jacques Izard, Didier Gonze, Leo Lahti and Rob Knight and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Karoline Faust

63 papers receiving 8.2k citations

Hit Papers

Microbial interactions: from networks to models 2012 2026 2016 2021 2012 2012 2016 2018 2020 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Karoline Faust Belgium 31 4.5k 3.6k 1.5k 834 689 65 8.3k
Ben Nichols United Kingdom 12 3.6k 0.8× 3.0k 0.9× 1.4k 0.9× 395 0.5× 571 0.8× 40 7.8k
Frédéric Mahé France 25 5.0k 1.1× 4.7k 1.3× 1.8k 1.2× 448 0.5× 656 1.0× 59 10.0k
Yanni Sun China 34 3.3k 0.7× 2.4k 0.7× 1.5k 1.0× 852 1.0× 673 1.0× 151 7.2k
Louise Fraser United Kingdom 6 3.4k 0.8× 2.4k 0.7× 942 0.6× 526 0.6× 788 1.1× 10 7.5k
Markus Bauer Austria 6 3.2k 0.7× 2.2k 0.6× 924 0.6× 526 0.6× 776 1.1× 9 6.9k
Folker Meyer United States 45 6.0k 1.3× 4.2k 1.2× 1.7k 1.1× 393 0.5× 949 1.4× 115 10.6k
Mark Rojas United States 11 4.6k 1.0× 2.8k 0.8× 870 0.6× 415 0.5× 822 1.2× 15 8.9k
Pengwei Hu China 27 5.8k 1.3× 2.7k 0.8× 1.1k 0.7× 415 0.5× 818 1.2× 120 11.3k
Ashley Shade United States 39 2.9k 0.6× 3.8k 1.1× 2.0k 1.4× 857 1.0× 760 1.1× 87 7.6k
Todd Z. DeSantis United States 25 3.0k 0.7× 3.0k 0.8× 2.3k 1.6× 727 0.9× 601 0.9× 29 8.1k

Countries citing papers authored by Karoline Faust

Since Specialization
Citations

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

Fields of papers citing papers by Karoline Faust

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Karoline Faust

This figure shows the co-authorship network connecting the top 25 collaborators of Karoline Faust. A scholar is included among the top collaborators of Karoline Faust 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 Karoline Faust. Karoline Faust 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
2.
Garza, Daniel, et al.. (2025). Emergence of alternative states in a synthetic human gut microbial community. Nature Communications. 17(1). 326–326.
3.
Garza, Daniel, et al.. (2024). Exploiting gut microbial traits and trade-offs in microbiome-based therapeutics. Nature Reviews Bioengineering. 2(5). 364–366. 2 indexed citations
4.
Bernaerts, Kristel, et al.. (2024). Predicting microbial interactions with approaches based on flux balance analysis: an evaluation. BMC Bioinformatics. 25(1). 36–36. 17 indexed citations
5.
Gao, Yu, et al.. (2023). miaSim: an R/Bioconductor package to easily simulate microbial community dynamics. Methods in Ecology and Evolution. 14(8). 1967–1980. 6 indexed citations
6.
Garza, Daniel, et al.. (2023). Metabolic models of human gut microbiota: Advances and challenges. Cell Systems. 14(2). 109–121. 14 indexed citations
7.
Liu, Bin, Daniel Garza, Didier Gonze, et al.. (2023). Starvation responses impact interaction dynamics of human gut bacteriaBacteroides thetaiotaomicronandRoseburia intestinalis. The ISME Journal. 17(11). 1940–1952. 12 indexed citations
8.
Sommeria‐Klein, Guilhem, et al.. (2022). Quantifying the impact of ecological memory on the dynamics of interacting communities. PLoS Computational Biology. 18(6). e1009396–e1009396. 20 indexed citations
9.
Huys, Geert, et al.. (2022). Fast quantification of gut bacterial species in cocultures using flow cytometry and supervised classification. ISME Communications. 2(1). 40–40. 14 indexed citations
10.
Krawczyk, Aleksandra I., Lisa Röttjers, Manoj Fonville, et al.. (2022). Quantitative microbial population study reveals geographical differences in bacterial symbionts of Ixodes ricinus. Microbiome. 10(1). 120–120. 25 indexed citations
11.
Cao, Xinyi, Dayong Zhao, Chaoran Li, et al.. (2021). Regime transition Shapes the Composition, Assembly Processes, and Co-occurrence Pattern of Bacterioplankton Community in a Large Eutrophic Freshwater Lake. Microbial Ecology. 84(2). 336–350. 6 indexed citations
12.
Deutschmann, Ina Maria, Gipsi Lima‐Mendez, Anders K. Krabberød, et al.. (2021). Disentangling environmental effects in microbial association networks. Microbiome. 9(1). 232–232. 28 indexed citations
13.
Vandeputte, Doris, Lindsey De Commer, Raúl Y. Tito, et al.. (2021). Temporal variability in quantitative human gut microbiome profiles and implications for clinical research. Nature Communications. 12(1). 6740–6740. 127 indexed citations
14.
McBain, Andrew J., Catherine O’Neill, Alejandro Amézquita, et al.. (2019). Consumer Safety Considerations of Skin and Oral Microbiome Perturbation. Clinical Microbiology Reviews. 32(4). 16 indexed citations
15.
Wang, Honggui, Zhong Wei, Lijuan Mei, et al.. (2016). Combined use of network inference tools identifies ecologically meaningful bacterial associations in a paddy soil. Soil Biology and Biochemistry. 105. 227–235. 64 indexed citations
16.
Bálint, Miklós, Mohammad Bahram, A. Murat Eren, et al.. (2016). Millions of reads, thousands of taxa: microbial community structure and associations analyzed via marker genes. FEMS Microbiology Reviews. 40(5). 686–700. 143 indexed citations
17.
Faust, Karoline, Leo Lahti, Didier Gonze, Willem M. de Vos, & Jeroen Raes. (2015). Metagenomics meets time series analysis: unraveling microbial community dynamics. Current Opinion in Microbiology. 25. 56–66. 280 indexed citations
18.
Edwards, Robert A., Katelyn McNair, Karoline Faust, Jeroen Raes, & Bas E. Dutilh. (2015). Computational approaches to predict bacteriophage–host relationships. FEMS Microbiology Reviews. 40(2). 258–272. 309 indexed citations
19.
Lozupone, Catherine, Karoline Faust, Jeroen Raes, et al.. (2012). Identifying genomic and metabolic features that can underlie early successional and opportunistic lifestyles of human gut symbionts. Genome Research. 22(10). 1974–1984. 108 indexed citations
20.
Faust, Karoline, Didier Croes, & Jacques van Helden. (2009). Metabolic Pathfinding Using RPAIR Annotation. Journal of Molecular Biology. 388(2). 390–414. 47 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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