Gregor Sturm

3.3k total citations · 1 hit paper
23 papers, 1.1k citations indexed

About

Gregor Sturm is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Gregor Sturm has authored 23 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 10 papers in Immunology and 7 papers in Oncology. Recurrent topics in Gregor Sturm's work include Single-cell and spatial transcriptomics (14 papers), Cancer Immunotherapy and Biomarkers (6 papers) and Immune Cell Function and Interaction (4 papers). Gregor Sturm is often cited by papers focused on Single-cell and spatial transcriptomics (14 papers), Cancer Immunotherapy and Biomarkers (6 papers) and Immune Cell Function and Interaction (4 papers). Gregor Sturm collaborates with scholars based in Austria, Germany and Netherlands. Gregor Sturm's co-authors include Francesca Finotello, Markus List, Jitao David Zhang, Jan Baumbach, Florent Petitprez, Tatsiana Aneichyk, Wolf H. Fridman, Zlatko Trajanoski, Sjoerd H. van der Burg and Dietmar Rieder and has published in prestigious journals such as Bioinformatics, International Journal of Molecular Sciences and Genome biology.

In The Last Decade

Gregor Sturm

21 papers receiving 1.1k citations

Hit Papers

Comprehensive evaluation of transcriptome-based cell-type... 2019 2026 2021 2023 2019 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gregor Sturm Austria 11 541 421 404 308 308 23 1.1k
Ya‐Ru Miao China 6 822 1.5× 419 1.0× 356 0.9× 530 1.7× 432 1.4× 6 1.4k
Weifeng Hong China 15 500 0.9× 304 0.7× 238 0.6× 263 0.9× 364 1.2× 52 925
Johannes Brägelmann Germany 16 557 1.0× 352 0.8× 122 0.3× 313 1.0× 296 1.0× 39 1.0k
Sun‐Hee Heo South Korea 22 537 1.0× 523 1.2× 435 1.1× 133 0.4× 191 0.6× 40 1.2k
Vanja Vaccaro Italy 15 491 0.9× 780 1.9× 188 0.5× 312 1.0× 301 1.0× 30 1.2k
Erbao Chen China 16 511 0.9× 520 1.2× 456 1.1× 315 1.0× 429 1.4× 37 1.3k
Xin Yi China 16 331 0.6× 359 0.9× 127 0.3× 288 0.9× 232 0.8× 66 837
Wenjun Qiu China 8 564 1.0× 288 0.7× 195 0.5× 411 1.3× 322 1.0× 16 991
Martin Rees United Kingdom 11 460 0.9× 490 1.2× 338 0.8× 111 0.4× 230 0.7× 17 973
Rilan Bai China 13 240 0.4× 567 1.3× 306 0.8× 247 0.8× 171 0.6× 36 920

Countries citing papers authored by Gregor Sturm

Since Specialization
Citations

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

Fields of papers citing papers by Gregor Sturm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gregor Sturm

This figure shows the co-authorship network connecting the top 25 collaborators of Gregor Sturm. A scholar is included among the top collaborators of Gregor Sturm 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 Gregor Sturm. Gregor Sturm 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.
Sturm, Gregor, et al.. (2025). Single-cell differential expression analysis between conditions within nested settings. Briefings in Bioinformatics. 26(4). 1 indexed citations
3.
Horvath, Lena, Agnieszka Martowicz, Gregor Sturm, et al.. (2024). Beyond binary: bridging neutrophil diversity to new therapeutic approaches in NSCLC. Trends in cancer. 10(5). 457–474. 17 indexed citations
4.
Sturm, Gregor, J A Kant, Nicholas McGranahan, et al.. (2024). Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion. iScience. 27(8). 110529–110529. 6 indexed citations
5.
Sturm, Gregor, et al.. (2024). Making mouse transcriptomics deconvolution accessible with immunedeconv. Bioinformatics Advances. 4(1). vbae032–vbae032. 2 indexed citations
6.
Stolzer, Iris, Susanne M. Krug, Elisabeth Naschberger, et al.. (2023). Proteolytic Activity of the Paracaspase MALT1 Is Involved in Epithelial Restitution and Mucosal Healing. International Journal of Molecular Sciences. 24(8). 7402–7402. 5 indexed citations
7.
Vieth, Michael, Gregor Sturm, Zlatko Trajanoski, et al.. (2023). Interleukin 36 receptor-inducible matrix metalloproteinase 13 mediates intestinal fibrosis. Frontiers in Immunology. 14. 1163198–1163198. 12 indexed citations
8.
Nguyen, Andrea, Gregor Sturm, Christina Plattner, et al.. (2023). P247 Oncostatin M and its receptor are markers of endoscopic and histological disease activity in Inflammatory Bowel Disease. Journal of Crohn s and Colitis. 17(Supplement_1). i397–i399. 1 indexed citations
9.
Sturm, Gregor, et al.. (2022). SimBu : bias-aware simulation of bulk RNA-seq data with variable cell-type composition. Bioinformatics. 38(Supplement_2). ii141–ii147. 16 indexed citations
10.
Sturm, Gregor, Markus List, & Jitao David Zhang. (2021). Tissue heterogeneity is prevalent in gene expression studies. NAR Genomics and Bioinformatics. 3(3). lqab077–lqab077. 7 indexed citations
11.
Sluijter, Marjolein, Gregor Sturm, Pornpimol Charoentong, et al.. (2021). NKG2A is a late immune checkpoint on CD8 T cells and marks repeated stimulation and cell division. International Journal of Cancer. 150(4). 688–704. 38 indexed citations
12.
Mascia, Fabrizio, Gregor Sturm, Anja A. Kühl, et al.. (2021). Dynamic, Transient, and Robust Increase in the Innervation of the Inflamed Mucosa in Inflammatory Bowel Diseases. Cells. 10(9). 2253–2253. 10 indexed citations
13.
Kortekaas, Kim E., Saskia J. Santegoets, Gregor Sturm, et al.. (2020). CD39 Identifies the CD4+ Tumor-Specific T-cell Population in Human Cancer. Cancer Immunology Research. 8(10). 1311–1321. 91 indexed citations
14.
Sturm, Gregor, Tamás Szabó, Georgios Fotakis, et al.. (2020). Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing data. Bioinformatics. 36(18). 4817–4818. 92 indexed citations
15.
Sturm, Gregor, Francesca Finotello, & Markus List. (2020). In Silico Cell-Type Deconvolution Methods in Cancer Immunotherapy. Methods in molecular biology. 2120. 213–222. 5 indexed citations
16.
Sturm, Gregor, Francesca Finotello, & Markus List. (2020). Immunedeconv: An R Package for Unified Access to Computational Methods for Estimating Immune Cell Fractions from Bulk RNA-Sequencing Data. Methods in molecular biology. 2120. 223–232. 166 indexed citations
17.
Sturm, Gregor, Francesca Finotello, Florent Petitprez, et al.. (2019). Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncology. Bioinformatics. 35(14). i436–i445. 569 indexed citations breakdown →
18.
Zhang, Jitao David, Klas Hatje, Gregor Sturm, et al.. (2017). Detect tissue heterogeneity in gene expression data with BioQC. BMC Genomics. 18(1). 277–277. 33 indexed citations
19.
Weinberger, Birgit, Andreas Kronbichler, Gregor Sturm, et al.. (2013). How immunosuppressive therapy affects T cells from kidney transplanted patients of different age: the role of latent cytomegalovirus infection. Clinical & Experimental Immunology. 176(1). 112–119. 5 indexed citations
20.
Knöll, Florian, Gregor Sturm, Claudia Lamina, et al.. (2011). Coumarins and survival in incident dialysis patients. Nephrology Dialysis Transplantation. 27(1). 332–337. 36 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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