Daniel Schimel

2.0k total citations · 1 hit paper
18 papers, 1.4k citations indexed

About

Daniel Schimel is a scholar working on Surgery, Radiology, Nuclear Medicine and Imaging and Epidemiology. According to data from OpenAlex, Daniel Schimel has authored 18 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Surgery, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Epidemiology. Recurrent topics in Daniel Schimel's work include Medical Imaging Techniques and Applications (3 papers), Tuberculosis Research and Epidemiology (3 papers) and Cancer, Hypoxia, and Metabolism (3 papers). Daniel Schimel is often cited by papers focused on Medical Imaging Techniques and Applications (3 papers), Tuberculosis Research and Epidemiology (3 papers) and Cancer, Hypoxia, and Metabolism (3 papers). Daniel Schimel collaborates with scholars based in United States, Slovakia and Germany. Daniel Schimel's co-authors include Toren Finkel, Calvin J. Kuo, Hongjun Liu, Marı́a M. Fergusson, J. Silvio Gutkind, Liu Cao, Rogério M. Castilho, Paul M. Hwang, Jie Liu and Ilsa I. Rovira and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Daniel Schimel

18 papers receiving 1.4k citations

Hit Papers

Augmented Wnt Signaling in a Mammalian Model of Accelerat... 2007 2026 2013 2019 2007 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Schimel United States 13 469 268 267 256 216 18 1.4k
Ashley Frazer‐Abel United States 22 550 1.2× 169 0.6× 136 0.5× 172 0.7× 199 0.9× 60 1.5k
Winson W. Tang United States 23 1.1k 2.4× 578 2.2× 463 1.7× 197 0.8× 163 0.8× 31 2.8k
Ruud J.T. Smeenk Netherlands 28 410 0.9× 253 0.9× 217 0.8× 59 0.2× 272 1.3× 66 3.1k
Jens Panse Germany 25 360 0.8× 244 0.9× 86 0.3× 185 0.7× 296 1.4× 154 2.2k
Minke G. Huitema Netherlands 32 415 0.9× 393 1.5× 148 0.6× 57 0.2× 187 0.9× 68 3.0k
Birgitta Gullstrand Sweden 27 706 1.5× 168 0.6× 165 0.6× 78 0.3× 146 0.7× 57 2.4k
Chengde Yang China 27 497 1.1× 242 0.9× 154 0.6× 120 0.5× 351 1.6× 122 2.1k
Daniel J. Birmingham United States 28 341 0.7× 547 2.0× 142 0.5× 60 0.2× 267 1.2× 66 2.4k
Yasuo Mori Japan 20 1.0k 2.2× 160 0.6× 118 0.4× 133 0.5× 252 1.2× 102 2.9k
Kammi Henriksen United States 19 348 0.7× 388 1.4× 463 1.7× 59 0.2× 146 0.7× 52 3.0k

Countries citing papers authored by Daniel Schimel

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Schimel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Schimel

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

All Works

18 of 18 papers shown
1.
Kauffman, Keith D., Michelle A. Sallin, Shunsuke Sakai, et al.. (2017). Defective positioning in granulomas but not lung-homing limits CD4 T-cell interactions with Mycobacterium tuberculosis-infected macrophages in rhesus macaques. Mucosal Immunology. 11(2). 462–473. 80 indexed citations
2.
Via, Laura E., Kathleen England, Dominique J. Wiener, et al.. (2015). A Sterilizing Tuberculosis Treatment Regimen Is Associated with Faster Clearance of Bacteria in Cavitary Lesions in Marmosets. Antimicrobial Agents and Chemotherapy. 59(7). 4181–4189. 47 indexed citations
3.
Datta, Meenal, Laura E. Via, Walid S. Kamoun, et al.. (2015). Anti-vascular endothelial growth factor treatment normalizes tuberculosis granuloma vasculature and improves small molecule delivery. Proceedings of the National Academy of Sciences. 112(6). 1827–1832. 158 indexed citations
4.
England, Kathleen, Helena I. Boshoff, Kriti Arora, et al.. (2012). Meropenem-Clavulanic Acid Shows Activity against Mycobacterium tuberculosis In Vivo. Antimicrobial Agents and Chemotherapy. 56(6). 3384–3387. 82 indexed citations
5.
Teng, Ruifeng, Oksana Gavrilova, Norio Suzuki, et al.. (2011). Disrupted erythropoietin signalling promotes obesity and alters hypothalamus proopiomelanocortin production. Nature Communications. 2(1). 520–520. 87 indexed citations
6.
Schimel, Daniel, et al.. (2010). Semi-automated method to measure pneumonia severity in mice through computed tomography (CT) scan analysis. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7624. 76241R–76241R. 1 indexed citations
7.
Martiniova, Lucia, et al.. (2009). In vivo micro-CT imaging of liver lesions in small animal models. Methods. 50(1). 20–25. 37 indexed citations
8.
Martiniova, Lucia, Melanie Kotys, David Thomasson, et al.. (2009). Noninvasive monitoring of a murine model of metastatic pheochromocytoma: A comparison of contrast‐enhanced microCT and nonenhanced MRI. Journal of Magnetic Resonance Imaging. 29(3). 685–691. 31 indexed citations
10.
Castrop, Hayo, Mona Oppermann, Diane Mizel, et al.. (2007). Skeletal abnormalities and extra-skeletal ossification in mice with restricted Gsα deletion caused by a renin promoter-Cre transgene. Cell and Tissue Research. 330(3). 487–501. 13 indexed citations
11.
Liu, Hongjun, Marı́a M. Fergusson, Rogério M. Castilho, et al.. (2007). Augmented Wnt Signaling in a Mammalian Model of Accelerated Aging. Science. 317(5839). 803–806. 604 indexed citations breakdown →
12.
Ohta, Shoichiro, Edwin W. Lai, John C. Morris, et al.. (2006). MicroCT for high‐resolution imaging of ectopic pheochromocytoma tumors in the liver of nude mice. International Journal of Cancer. 119(9). 2236–2241. 26 indexed citations
13.
Martiniova, Lucia, Shoichiro Ohta, Peter Guion, et al.. (2006). Anatomical and Functional Imaging of Tumors in Animal Models. Annals of the New York Academy of Sciences. 1073(1). 392–404. 10 indexed citations
14.
Singh, Arun S., Gordon R. Macpherson, Douglas K. Price, Daniel Schimel, & William D. Figg. (2006). Evaluation of human fetal bone implants in SCID mice as a model of prostate cancer bone metastasis. Oncology Reports. 15(3). 519–24. 6 indexed citations
15.
Hsu, Lewis L., Hunter C. Champion, Sally A. Campbell‐Lee, et al.. (2006). Hemolysis in Sickle Cell Mice Causes Pulmonary Hypertension Due to Global Impairment in Nitric Oxide Bioavailability.. Blood. 108(11). 785–785. 10 indexed citations
16.
Hsu, Lewis L., Hunter C. Champion, Sally A. Campbell‐Lee, et al.. (2006). Hemolysis in sickle cell mice causes pulmonary hypertension due to global impairment in nitric oxide bioavailability. Blood. 109(7). 3088–3098. 200 indexed citations
18.
Sugaya, Makoto, Takahiro Watanabe, Matthew F. Starost, et al.. (2004). Lymphatic dysfunction in transgenic mice expressing KSHV k-cyclin under the control of the VEGFR-3 promoter. Blood. 105(6). 2356–2363. 30 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026