Bo Marelli

912 total citations · 1 hit paper
8 papers, 557 citations indexed

About

Bo Marelli is a scholar working on Oncology, Immunology and Molecular Biology. According to data from OpenAlex, Bo Marelli has authored 8 papers receiving a total of 557 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 4 papers in Immunology and 2 papers in Molecular Biology. Recurrent topics in Bo Marelli's work include Immunotherapy and Immune Responses (4 papers), Cancer Immunotherapy and Biomarkers (4 papers) and Cancer Research and Treatments (2 papers). Bo Marelli is often cited by papers focused on Immunotherapy and Immune Responses (4 papers), Cancer Immunotherapy and Biomarkers (4 papers) and Cancer Research and Treatments (2 papers). Bo Marelli collaborates with scholars based in United States, Italy and Germany. Bo Marelli's co-authors include Yan Lan, Kin-Ming Lo, Guozhong Qin, Jin Qi, Chunxiao Xu, Huakui Yu, Laszlo Radvanyi, Helen Sabzevari, Kenneth W. Hance and Dong Zhang and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and The Journal of Immunology.

In The Last Decade

Bo Marelli

8 papers receiving 545 citations

Hit Papers

Enhanced preclinical antitumor activity of M7824, a bifun... 2018 2026 2020 2023 2018 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bo Marelli United States 5 415 281 161 64 52 8 557
Molly H. Jenkins United States 8 399 1.0× 237 0.8× 184 1.1× 63 1.0× 45 0.9× 11 552
George Locke United States 6 336 0.8× 187 0.7× 239 1.5× 69 1.1× 30 0.6× 9 540
Lillian Sun United States 7 378 0.9× 298 1.1× 120 0.7× 63 1.0× 29 0.6× 9 508
Alexandro Landshammer Germany 6 322 0.8× 229 0.8× 122 0.8× 81 1.3× 42 0.8× 8 476
Axel Lechner Germany 12 435 1.0× 328 1.2× 135 0.8× 94 1.5× 21 0.4× 28 660
Rikke Løvendahl Eefsen Denmark 11 375 0.9× 165 0.6× 158 1.0× 82 1.3× 72 1.4× 32 624
Sangeeta Kakoti Japan 7 500 1.2× 262 0.9× 243 1.5× 119 1.9× 42 0.8× 12 647
Philippe De La Rochère France 6 206 0.5× 202 0.7× 149 0.9× 40 0.6× 31 0.6× 7 478
Antonina Avanzi United States 6 352 0.8× 368 1.3× 109 0.7× 42 0.7× 23 0.4× 7 591
Trinh Pham United States 7 307 0.7× 234 0.8× 132 0.8× 95 1.5× 32 0.6× 11 528

Countries citing papers authored by Bo Marelli

Since Specialization
Citations

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

Fields of papers citing papers by Bo Marelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bo Marelli

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

All Works

8 of 8 papers shown
1.
Jiang, Feng, Jin Qi, Huakui Yu, et al.. (2023). Effect of extended treatment with IAP inhibitor xevinapant post radiotherapy (RT) on efficacy and the tumor microenvironment (TME) in preclinical models.. Journal of Clinical Oncology. 41(16_suppl). 6027–6027. 2 indexed citations
2.
Jiang, Feng, Hong Wang, Tsz-Lun Yeung, et al.. (2021). 609 Combining bintrafusp alfa with abituzumab enhances suppression of the TGF-β signaling pathway. SHILAP Revista de lepidopterología. A639–A639. 1 indexed citations
3.
Xu, Chunxiao, Bo Marelli, Jin Qi, et al.. (2021). NHS-IL12 and bintrafusp alfa combination therapy enhances antitumor activity in preclinical cancer models. Translational Oncology. 16. 101322–101322. 12 indexed citations
4.
Lan, Yan, Dong Zhang, Chunxiao Xu, et al.. (2018). Enhanced preclinical antitumor activity of M7824, a bifunctional fusion protein simultaneously targeting PD-L1 and TGF-β. Science Translational Medicine. 10(424). 405 indexed citations breakdown →
5.
Xu, Chunxiao, Yanping Zhang, Alex Rolfe, et al.. (2017). Combination Therapy with NHS-muIL12 and Avelumab (anti-PD-L1) Enhances Antitumor Efficacy in Preclinical Cancer Models. Clinical Cancer Research. 23(19). 5869–5880. 58 indexed citations
6.
Lan, Yan, Dong Zhang, Chunxiao Xu, et al.. (2017). Abstract 2615: Preclinical evaluation and mechanistic characterization of M7824 (MSB0011359C), a novel bifunctional fusion protein targeting the PD-L1 and TGFβ pathways. Cancer Research. 77(13_Supplement). 2615–2615. 4 indexed citations
7.
Waight, Jeremy D., Shinji Takai, Bo Marelli, et al.. (2014). Cutting Edge: Epigenetic Regulation of Foxp3 Defines a Stable Population of CD4+ Regulatory T Cells in Tumors from Mice and Humans. The Journal of Immunology. 194(3). 878–882. 47 indexed citations
8.
Way, Jeffrey C., Scott Lauder, Beatrice Brunkhorst, et al.. (2005). Improvement of Fc–erythropoietin structure and pharmacokinetics by modification at a disulfide bond. Protein Engineering Design and Selection. 18(3). 111–118. 28 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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