Richard J. Sové

629 total citations
17 papers, 447 citations indexed

About

Richard J. Sové is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Richard J. Sové has authored 17 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 4 papers in Molecular Biology and 4 papers in Immunology. Recurrent topics in Richard J. Sové's work include Cancer Immunotherapy and Biomarkers (5 papers), Mathematical Biology Tumor Growth (4 papers) and CAR-T cell therapy research (3 papers). Richard J. Sové is often cited by papers focused on Cancer Immunotherapy and Biomarkers (5 papers), Mathematical Biology Tumor Growth (4 papers) and CAR-T cell therapy research (3 papers). Richard J. Sové collaborates with scholars based in United States and Canada. Richard J. Sové's co-authors include Aleksander S. Popel, Hanwen Wang, Huilin Ma, Chen Zhao, Mohammad Jafarnejad, Joseph R. Stinziano, Brent J. Sinclair, Howard D. Rundle, Brian H. Annex and Craig Giragossian and has published in prestigious journals such as PLoS ONE, Scientific Reports and PLoS Computational Biology.

In The Last Decade

Richard J. Sové

16 papers receiving 441 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Richard J. Sové United States 11 180 138 101 85 77 17 447
Irineu Illa-Bochaca United States 12 190 1.1× 121 0.9× 35 0.3× 7 0.1× 74 1.0× 22 371
Gerald R. Thrush United States 8 201 1.1× 137 1.0× 242 2.4× 29 0.3× 51 0.7× 11 474
Elitza Markova-Car Croatia 12 24 0.1× 71 0.5× 46 0.5× 13 0.2× 17 0.2× 21 380
Steven N. Steinway United States 12 207 1.1× 459 3.3× 65 0.6× 33 0.4× 104 1.4× 19 731
S. Chwalinski United Kingdom 10 169 0.9× 126 0.9× 65 0.6× 24 0.3× 28 0.4× 14 389
Margriet M. Palm Netherlands 5 53 0.3× 90 0.7× 48 0.5× 72 0.8× 23 0.3× 8 274
Michaela Bayerlová Germany 12 91 0.5× 263 1.9× 40 0.4× 3 0.0× 93 1.2× 14 405
B. Maurer‐Schultze Germany 11 83 0.5× 188 1.4× 31 0.3× 21 0.2× 60 0.8× 38 418
Xiao Fu United Kingdom 10 28 0.2× 124 0.9× 9 0.1× 20 0.2× 18 0.2× 28 306
Sixue Liu China 12 119 0.7× 153 1.1× 79 0.8× 6 0.1× 68 0.9× 34 359

Countries citing papers authored by Richard J. Sové

Since Specialization
Citations

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

Fields of papers citing papers by Richard J. Sové

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard J. Sové. 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 Richard J. Sové. The network helps show where Richard J. Sové may publish in the future.

Co-authorship network of co-authors of Richard J. Sové

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

All Works

17 of 17 papers shown
1.
Sové, Richard J., et al.. (2022). Virtual clinical trials of anti-PD-1 and anti-CTLA-4 immunotherapy in advanced hepatocellular carcinoma using a quantitative systems pharmacology model. Journal for ImmunoTherapy of Cancer. 10(11). e005414–e005414. 32 indexed citations
2.
Gong, Chang, Hanwen Wang, Richard J. Sové, et al.. (2022). Simulations of tumor growth and response to immunotherapy by coupling a spatial agent-based model with a whole-patient quantitative systems pharmacology model. PLoS Computational Biology. 18(7). e1010254–e1010254. 36 indexed citations
3.
Sové, Richard J., et al.. (2022). Spectroscopy detects skeletal muscle microvascular dysfunction during onset of sepsis in a rat fecal peritonitis model. Scientific Reports. 12(1). 6339–6339. 9 indexed citations
4.
5.
Wang, Hanwen, Huilin Ma, Richard J. Sové, Leisha A. Emens, & Aleksander S. Popel. (2021). Quantitative systems pharmacology model predictions for efficacy of atezolizumab and nab-paclitaxel in triple-negative breast cancer. Journal for ImmunoTherapy of Cancer. 9(2). e002100–e002100. 38 indexed citations
6.
Zhao, Chen, et al.. (2021). A data-driven computational model enables integrative and mechanistic characterization of dynamic macrophage polarization. iScience. 24(2). 102112–102112. 31 indexed citations
7.
Sové, Richard J., et al.. (2021). Localized Oxygen Exchange Platform for Intravital Video Microscopy Investigations of Microvascular Oxygen Regulation. Frontiers in Physiology. 12. 654928–654928. 5 indexed citations
8.
Sové, Richard J., Mohammad Jafarnejad, Chen Zhao, et al.. (2020). QSP‐IO: A Quantitative Systems Pharmacology Toolbox for Mechanistic Multiscale Modeling for Immuno‐Oncology Applications. CPT Pharmacometrics & Systems Pharmacology. 9(9). 484–497. 43 indexed citations
9.
Ma, Huilin, Hanwen Wang, Richard J. Sové, et al.. (2020). A Quantitative Systems Pharmacology Model of T Cell Engager Applied to Solid Tumor. The AAPS Journal. 22(4). 85–85. 29 indexed citations
10.
Wang, Hanwen, Richard J. Sové, Mohammad Jafarnejad, et al.. (2020). Conducting a Virtual Clinical Trial in HER2-Negative Breast Cancer Using a Quantitative Systems Pharmacology Model With an Epigenetic Modulator and Immune Checkpoint Inhibitors. Frontiers in Bioengineering and Biotechnology. 8. 40 indexed citations
11.
Ma, Huilin, Hanwen Wang, Richard J. Sové, et al.. (2020). Combination therapy with T cell engager and PD-L1 blockade enhances the antitumor potency of T cells as predicted by a QSP model. Journal for ImmunoTherapy of Cancer. 8(2). e001141–e001141. 38 indexed citations
12.
Zhao, Chen, et al.. (2019). A mechanistic integrative computational model of macrophage polarization: Implications in human pathophysiology. PLoS Computational Biology. 15(11). e1007468–e1007468. 43 indexed citations
13.
Jafarnejad, Mohammad, Richard J. Sové, Ludmila Danilova, et al.. (2019). Mechanistically detailed systems biology modeling of the HGF/Met pathway in hepatocellular carcinoma. npj Systems Biology and Applications. 5(1). 29–29. 21 indexed citations
14.
Sové, Richard J., Daniel Goldman, & Graham Fraser. (2016). A computational model of the effect of capillary density variability on oxygen transport, glucose uptake, and insulin sensitivity in prediabetes. Microcirculation. 24(2). 5 indexed citations
15.
Sové, Richard J., Graham Fraser, Daniel Goldman, & Christopher G. Ellis. (2016). Finite Element Model of Oxygen Transport for the Design of Geometrically Complex Microfluidic Devices Used in Biological Studies. PLoS ONE. 11(11). e0166289–e0166289. 6 indexed citations
16.
Stinziano, Joseph R., Richard J. Sové, Howard D. Rundle, & Brent J. Sinclair. (2014). Rapid desiccation hardening changes the cuticular hydrocarbon profile of Drosophila melanogaster. Comparative Biochemistry and Physiology Part A Molecular & Integrative Physiology. 180. 38–42. 65 indexed citations
17.
Sové, Richard J., et al.. (2013). A Computational Model of a Microfluidic Device to Measure the Dynamics of Oxygen-Dependent ATP Release from Erythrocytes. PLoS ONE. 8(11). e81537–e81537. 6 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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