Julia Schueler

768 total citations
34 papers, 406 citations indexed

About

Julia Schueler is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Julia Schueler has authored 34 papers receiving a total of 406 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Oncology, 8 papers in Molecular Biology and 8 papers in Immunology. Recurrent topics in Julia Schueler's work include Cancer Cells and Metastasis (10 papers), 3D Printing in Biomedical Research (6 papers) and Immunotherapy and Immune Responses (5 papers). Julia Schueler is often cited by papers focused on Cancer Cells and Metastasis (10 papers), 3D Printing in Biomedical Research (6 papers) and Immunotherapy and Immune Responses (5 papers). Julia Schueler collaborates with scholars based in Germany, Canada and United Kingdom. Julia Schueler's co-authors include Gabrielle M. Siegers, Heinz‐Herbert Fiebig, Shuji Tohda, Xinghua Wang, Jeffrey A. Medin, Paul Fisch, Yoko Kosaka, Helena Dhamko, Armand Keating and Tania C. Felizardo and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Blood.

In The Last Decade

Julia Schueler

30 papers receiving 398 citations

Peers

Julia Schueler
Rochelle Fletcher United States
Se Jin Oh South Korea
Sanket More Belgium
Neale T. Hanke United States
Jeremy Griggs United Kingdom
You-Soo Park South Korea
Julia Schueler
Citations per year, relative to Julia Schueler Julia Schueler (= 1×) peers Maria Teresa Bilotta

Countries citing papers authored by Julia Schueler

Since Specialization
Citations

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

Fields of papers citing papers by Julia Schueler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julia Schueler

This figure shows the co-authorship network connecting the top 25 collaborators of Julia Schueler. A scholar is included among the top collaborators of Julia Schueler 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 Julia Schueler. Julia Schueler 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.
Schueler, Julia, et al.. (2025). Spatial Proteomics by Parallel Accumulation‐Serial Fragmentation Supported MALDI MS/MS Imaging: A First Glance Into Multiplexed and Spatial Peptide Identification. Rapid Communications in Mass Spectrometry. 39(9). e10006–e10006. 2 indexed citations
2.
Grassi, Elena, Aikaterini Chatzipli, Emre Karakoç, et al.. (2024). Integrative ensemble modelling of cetuximab sensitivity in colorectal cancer patient-derived xenografts. Nature Communications. 15(1). 9139–9139. 5 indexed citations
4.
Dong, Meng, Kathrin Böpple, Bernd Winkler, et al.. (2023). Perfusion Air Culture of Precision-Cut Tumor Slices: An Ex Vivo System to Evaluate Individual Drug Response under Controlled Culture Conditions. Cells. 12(5). 807–807. 7 indexed citations
5.
Oswald, Eva, Anne Grote, Nassim Bouteldja, et al.. (2022). Immune cell infiltration pattern in non-small cell lung cancer PDX models is a model immanent feature and correlates with a distinct molecular and phenotypic make-up. Journal for ImmunoTherapy of Cancer. 10(4). e004412–e004412. 10 indexed citations
6.
Ali, Zaheer, Gabriela Vazquez Rodriguez, Ioannis Vamvakaris, et al.. (2022). Zebrafish patient-derived xenograft models predict lymph node involvement and treatment outcome in non-small cell lung cancer. Journal of Experimental & Clinical Cancer Research. 41(1). 58–58. 31 indexed citations
7.
Schueler, Julia, Jeffrey T. Borenstein, Meng Dong, et al.. (2022). How to build a tumor: An industry perspective. Drug Discovery Today. 27(10). 103329–103329. 5 indexed citations
8.
Newell, Marnie, Susan Goruk, Julia Schueler, et al.. (2022). Docosahexaenoic acid enrichment of tumor phospholipid membranes increases tumor necroptosis in mice bearing triple negative breast cancer patient-derived xenografts. The Journal of Nutritional Biochemistry. 107. 109018–109018. 14 indexed citations
9.
Papatzimas, James W., Julia Schueler, Darren J. Derksen, et al.. (2020). ADAM protease inhibition overcomes resistance of breast cancer stem-like cells to γδ T cell immunotherapy. Cancer Letters. 496. 156–168. 13 indexed citations
10.
Miller, Christopher H., et al.. (2020). A novel chemotactic factor derived from the extracellular matrix protein decorin recruits mesenchymal stromal cells in vitro and in vivo. PLoS ONE. 15(7). e0235784–e0235784. 16 indexed citations
11.
Schueler, Julia, et al.. (2020). Modeling Immune Checkpoint Inhibitor Efficacy in Syngeneic Mouse Tumors in an Ex Vivo Immuno-Oncology Dynamic Environment. International Journal of Molecular Sciences. 21(18). 6478–6478. 8 indexed citations
12.
Jang, Jiryeon, Oliver Rath, Julia Schueler, et al.. (2017). Development of Novel Patient-Derived Preclinical Models from Malignant Effusions in Patients with Tyrosine Kinase Inhibitor–Resistant Clear Cell Renal Cell Carcinoma. Translational Oncology. 10(3). 304–310. 3 indexed citations
13.
Kim, Sun Young, Su Jin Lee, Seung Tae Kim, et al.. (2016). BEZ235 (PIK3/mTOR inhibitor) Overcomes Pazopanib Resistance in Patient-Derived Refractory Soft Tissue Sarcoma Cells. Translational Oncology. 9(3). 197–202. 10 indexed citations
14.
Tomiuk, Stefan, Stefan M. Wild, Silvia Rüberg, et al.. (2016). Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells. Journal of Visualized Experiments.
15.
Tomiuk, Stefan, Stefan Wild, Silvia Rüberg, et al.. (2016). Depletion of Mouse Cells from Human Tumor Xenografts Significantly Improves Downstream Analysis of Target Cells. Journal of Visualized Experiments. 7 indexed citations
16.
Davies, Emma Jane, Meng Dong, Matthias Gutekunst, et al.. (2015). Capturing complex tumour biology in vitro: histological and molecular characterisation of precision cut slices. Scientific Reports. 5(1). 17187–17187. 92 indexed citations
17.
Schueler, Julia, Michael Haerter, Ulf Boemer, et al.. (2014). Abstract 1026: Novel Tie2 inhibitor with in vivo efficacy in disseminated hematological tumor models in mice. Cancer Research. 74(19_Supplement). 1026–1026. 1 indexed citations
18.
Schueler, Julia, Dagmar Wider, Gabrielle M. Siegers, et al.. (2013). Intratibial Injection of Human Multiple Myeloma Cells in NOD/SCID IL-2Rγ(Null) Mice Mimics Human Myeloma and Serves as a Valuable Tool for the Development of Anticancer Strategies. PLoS ONE. 8(11). e79939–e79939. 21 indexed citations
19.
Siegers, Gabrielle M., Helena Dhamko, Xinghua Wang, et al.. (2011). Human Vδ1 γδ T cells expanded from peripheral blood exhibit specific cytotoxicity against B-cell chronic lymphocytic leukemia-derived cells. Cytotherapy. 13(6). 753–764. 79 indexed citations
20.
Giesemann, Torsten, Julia Schueler, Vincent Vuaroqueaux, et al.. (2010). 634 Patient-derived breast cancer xenografts: Molecular characteristics and growth properties. European Journal of Cancer Supplements. 8(7). 198–199. 1 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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