Mark Prytyskach

556 total citations
9 papers, 450 citations indexed

About

Mark Prytyskach is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Mark Prytyskach has authored 9 papers receiving a total of 450 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Oncology and 4 papers in Immunology. Recurrent topics in Mark Prytyskach's work include Phagocytosis and Immune Regulation (3 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Cancer Research and Treatments (2 papers). Mark Prytyskach is often cited by papers focused on Phagocytosis and Immune Regulation (3 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Cancer Research and Treatments (2 papers). Mark Prytyskach collaborates with scholars based in United States, Austria and Switzerland. Mark Prytyskach's co-authors include Miles A. Miller, Ralph Weissleder, Rainer H. Köhler, Ran Li, Thomas S.C. Ng, Christopher B. Rodell, Hannes Mikula, Mikäel J. Pittet, Matthias Nahrendorf and Gabriel Courties and has published in prestigious journals such as Nature Communications, ACS Nano and Nature Nanotechnology.

In The Last Decade

Mark Prytyskach

9 papers receiving 445 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark Prytyskach United States	9	207	169	113	102	95	9	450
Giulia Pellizzari United Kingdom	8	253 1.2×	111 0.7×	143 1.3×	105 1.0×	160 1.7×	12	570
Shweta Sharma United States	9	259 1.3×	179 1.1×	53 0.5×	215 2.1×	101 1.1×	11	491
Yinghao Ding China	11	187 0.9×	146 0.9×	57 0.5×	157 1.5×	52 0.5×	20	351
Dianlong Jia China	12	180 0.9×	104 0.6×	57 0.5×	80 0.8×	79 0.8×	27	357
Paula Díez Spain	13	257 1.2×	76 0.4×	56 0.5×	45 0.4×	56 0.6×	43	452
Derek Reichel United States	10	208 1.0×	205 1.2×	90 0.8×	180 1.8×	86 0.9×	18	508
Micah John Luderer United States	12	222 1.1×	107 0.6×	61 0.5×	76 0.7×	160 1.7×	15	592
Kinan Alhallak United States	11	155 0.7×	116 0.7×	125 1.1×	47 0.5×	109 1.1×	25	463
Danfeng Luo China	17	328 1.6×	159 0.9×	106 0.9×	66 0.6×	160 1.7×	31	659
Melissa Loren United States	6	245 1.2×	84 0.5×	103 0.9×	39 0.4×	98 1.0×	6	449

Countries citing papers authored by Mark Prytyskach

Since Specialization

Citations

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

Fields of papers citing papers by Mark Prytyskach

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Prytyskach

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

All Works

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9 of 9 papers shown

Li, Ran, Thomas S.C. Ng, Stephanie J. Wang, et al.. (2021). Therapeutically reprogrammed nutrient signalling enhances nanoparticulate albumin bound drug uptake and efficacy in KRAS-mutant cancer. Nature Nanotechnology. 16(7). 830–839. 94 indexed citations

Stewart-Ornstein, Jacob, Yoshiko Iwamoto, Miles A. Miller, et al.. (2021). p53 dynamics vary between tissues and are linked with radiation sensitivity. Nature Communications. 12(1). 898–898. 54 indexed citations

Li, Ran, Stephanie Wang, Mark Prytyskach, et al.. (2020). In vivo microscopy reveals macrophage polarization locally promotes coherent microtubule dynamics in migrating cancer cells. Nature Communications. 11(1). 3521–3521. 19 indexed citations

Wang, Stephanie J., Ran Li, Thomas S.C. Ng, et al.. (2020). Efficient blockade of locally reciprocated tumor-macrophage signaling using a TAM-avid nanotherapy. Science Advances. 6(21). eaaz8521–eaaz8521. 24 indexed citations

Ng, Thomas S.C., Viswanath Gunda, Ran Li, et al.. (2020). Detecting Immune Response to Therapies Targeting PDL1 and BRAF by Using Ferumoxytol MRI and Macrin in Anaplastic Thyroid Cancer. Radiology. 298(1). 123–132. 22 indexed citations

Li, Ran, et al.. (2019). Single‐Cell Intravital Microscopy of Trastuzumab Quantifies Heterogeneous in vivo Kinetics. Cytometry Part A. 97(5). 528–539. 15 indexed citations

Miller, Miles A., Hannes Mikula, Ran Li, et al.. (2018). Modular Nanoparticulate Prodrug Design Enables Efficient Treatment of Solid Tumors Using Bioorthogonal Activation. ACS Nano. 12(12). 12814–12826. 84 indexed citations

Kim, Hye-Yeong, Ran Li, Thomas S.C. Ng, et al.. (2018). Quantitative Imaging of Tumor-Associated Macrophages and Their Response to Therapy Using ⁶⁴Cu-Labeled Macrin. ACS Nano. 12(12). 12015–12029. 117 indexed citations

Miller, Miles A., Eunha Kim, Michael F. Cuccarese, et al.. (2017). Near infrared imaging of Mer tyrosine kinase (MERTK) using MERi-SiR reveals tumor associated macrophage uptake in metastatic disease. Chemical Communications. 54(1). 42–45. 21 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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