Jean‐Marc Schwartz

3.8k total citations
110 papers, 2.7k citations indexed

About

Jean‐Marc Schwartz is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, Jean‐Marc Schwartz has authored 110 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Molecular Biology, 20 papers in Cell Biology and 12 papers in Oncology. Recurrent topics in Jean‐Marc Schwartz's work include Microbial Metabolic Engineering and Bioproduction (30 papers), Bioinformatics and Genomic Networks (29 papers) and Gene Regulatory Network Analysis (15 papers). Jean‐Marc Schwartz is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (30 papers), Bioinformatics and Genomic Networks (29 papers) and Gene Regulatory Network Analysis (15 papers). Jean‐Marc Schwartz collaborates with scholars based in United Kingdom, Japan and Germany. Jean‐Marc Schwartz's co-authors include Günther Gerisch, Jose C. Nacher, Giles N. Johnson, Monika Westphal, Minoru Kanehisa, Ray Boot-Handford, Jamie Soul, Tim Hardingham, Sara Dunn and Sanjay Anand and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Jean‐Marc Schwartz

105 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jean‐Marc Schwartz United Kingdom 30 1.4k 672 297 229 200 110 2.7k
Sabine Fischer Germany 36 1.3k 0.9× 213 0.3× 431 1.5× 562 2.5× 144 0.7× 159 4.2k
Jonathan S. Minden United States 25 2.6k 1.9× 631 0.9× 191 0.6× 259 1.1× 38 0.2× 59 3.6k
Tong Hao China 28 3.6k 2.6× 403 0.6× 575 1.9× 181 0.8× 91 0.5× 75 5.7k
Rachel J. Errington United Kingdom 27 1.9k 1.4× 229 0.3× 284 1.0× 112 0.5× 78 0.4× 110 2.8k
Mathias Walzer Germany 13 3.2k 2.3× 467 0.7× 152 0.5× 316 1.4× 60 0.3× 20 4.9k
Tetsuya Kobayashi Japan 33 1.3k 1.0× 179 0.3× 129 0.4× 390 1.7× 170 0.8× 219 4.2k
Dorothea Busse Germany 6 3.6k 2.6× 444 0.7× 128 0.4× 247 1.1× 57 0.3× 7 5.1k
Heimo Wolinski Austria 35 2.5k 1.8× 759 1.1× 440 1.5× 554 2.4× 46 0.2× 87 5.0k
Jin Yu China 32 2.4k 1.7× 131 0.2× 219 0.7× 115 0.5× 99 0.5× 156 3.7k
David Lee United States 27 2.0k 1.4× 284 0.4× 97 0.3× 217 0.9× 35 0.2× 76 3.1k

Countries citing papers authored by Jean‐Marc Schwartz

Since Specialization
Citations

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

Fields of papers citing papers by Jean‐Marc Schwartz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean‐Marc Schwartz. 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 Jean‐Marc Schwartz. The network helps show where Jean‐Marc Schwartz may publish in the future.

Co-authorship network of co-authors of Jean‐Marc Schwartz

This figure shows the co-authorship network connecting the top 25 collaborators of Jean‐Marc Schwartz. A scholar is included among the top collaborators of Jean‐Marc Schwartz 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 Jean‐Marc Schwartz. Jean‐Marc Schwartz 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.
Rosser, Susan J., Andrew R. Pitt, Tessa Moses, et al.. (2025). Flux Sampling Suggests Metabolic Signatures of High Antibody‐Producing CHO Cells. Biotechnology and Bioengineering. 122(7). 1898–1913.
2.
Schwartz, Jean‐Marc, et al.. (2024). Functional selectivity of Receptor Tyrosine Kinases regulates distinct cellular outputs. Frontiers in Cell and Developmental Biology. 11. 1348056–1348056. 4 indexed citations
3.
Akutsu, Tatsuya, et al.. (2024). A practically efficient algorithm for identifying critical control proteins in directed probabilistic biological networks. npj Systems Biology and Applications. 10(1). 87–87. 1 indexed citations
4.
Akutsu, Tatsuya, et al.. (2024). Measuring criticality in control of complex biological networks. npj Systems Biology and Applications. 10(1). 9–9. 2 indexed citations
5.
6.
Hayes, Kelly S., et al.. (2023). A genome-scale metabolic model of parasitic whipworm. Nature Communications. 14(1). 6937–6937. 5 indexed citations
7.
Ferguson, Jennifer, David Knight, Gareth Howell, et al.. (2022). Spatially resolved phosphoproteomics reveals fibroblast growth factor receptor recycling-driven regulation of autophagy and survival. Nature Communications. 13(1). 6589–6589. 13 indexed citations
8.
Schwartz, Jean‐Marc, et al.. (2022). A calpain-6/YAP axis in sarcoma stem cells that drives the outgrowth of tumors and metastases. Cell Death and Disease. 13(9). 819–819. 1 indexed citations
9.
Calzadilla, Pablo Ignacio, et al.. (2021). Cytosolic fumarase acts as a metabolic fail-safe for both high and low temperature acclimation of Arabidopsis thaliana. Journal of Experimental Botany. 73(7). 2112–2124. 5 indexed citations
10.
Jones, Matt, et al.. (2021). Combinatorial mathematical modelling approaches to interrogate rear retraction dynamics in 3D cell migration. PLoS Computational Biology. 17(3). e1008213–e1008213. 6 indexed citations
11.
12.
Schwartz, Jean‐Marc, et al.. (2020). HybridMine: A Pipeline for Allele Inheritance and Gene Copy Number Prediction in Hybrid Genomes and Its Application to Industrial Yeasts. Microorganisms. 8(10). 1554–1554. 7 indexed citations
13.
Nacher, Jose C., et al.. (2019). Network controllability analysis of intracellular signalling reveals viruses are actively controlling molecular systems. Scientific Reports. 9(1). 2066–2066. 18 indexed citations
14.
Schwartz, Jean‐Marc, et al.. (2019). Probabilistic controllability approach to metabolic fluxes in normal and cancer tissues. Nature Communications. 10(1). 2725–2725. 13 indexed citations
15.
Elson, Ari, et al.. (2019). Kinetic Modeling of DUSP Regulation in Herceptin-Resistant HER2-Positive Breast Cancer. Genes. 10(8). 568–568. 2 indexed citations
16.
Soul, Jamie, Tim Hardingham, Ray Boot-Handford, & Jean‐Marc Schwartz. (2018). SkeletalVis: an exploration and meta-analysis data portal of cross-species skeletal transcriptomics data. Bioinformatics. 35(13). 2283–2290. 17 indexed citations
17.
Mutti, Luciano, et al.. (2017). Insight into glucocorticoid receptor signalling through interactome model analysis. PLoS Computational Biology. 13(11). e1005825–e1005825. 7 indexed citations
18.
Wu, Chengkun, Jean‐Marc Schwartz, Georg Brabant, & Goran Nenadić. (2014). Molecular profiling of thyroid cancer subtypes using large-scale text mining. BMC Medical Genomics. 7(S3). S3–S3. 10 indexed citations
19.
Schwartz, Jean‐Marc, et al.. (2009). Deterministic mathematical models of the cAMP pathway in Saccharomyces cerevisiae. BMC Systems Biology. 3(1). 70–70. 14 indexed citations
20.
Westphal, Monika, et al.. (1997). Microfilament dynamics during cell movement and chemotaxis monitored using a GFP–actin fusion protein. Current Biology. 7(3). 176–183. 222 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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