Max Kullberg

1.4k total citations · 1 hit paper
31 papers, 1.1k citations indexed

About

Max Kullberg is a scholar working on Molecular Biology, Immunology and Analytical Chemistry. According to data from OpenAlex, Max Kullberg has authored 31 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 8 papers in Immunology and 6 papers in Analytical Chemistry. Recurrent topics in Max Kullberg's work include RNA Interference and Gene Delivery (10 papers), Immunotherapy and Immune Responses (6 papers) and Analytical Chemistry and Chromatography (5 papers). Max Kullberg is often cited by papers focused on RNA Interference and Gene Delivery (10 papers), Immunotherapy and Immune Responses (6 papers) and Analytical Chemistry and Chromatography (5 papers). Max Kullberg collaborates with scholars based in United States, Bulgaria and Germany. Max Kullberg's co-authors include Thomas J. Anchordoquy, Tyson Smyth, Michael W. Graner, Noeen Malik, Peter Smith‐Jones, Kristine Mann, Charles W. Gorodetzky, O. N. Hinsvark, Ryan L. McCarthy and Jerome Edelson and has published in prestigious journals such as Cancer Research, International Journal of Molecular Sciences and Biophysical Journal.

In The Last Decade

Max Kullberg

30 papers receiving 1.1k citations

Hit Papers

Biodistribution and delivery efficiency of unmodified tum... 2014 2026 2018 2022 2014 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
Max Kullberg United States 17 796 362 227 146 143 31 1.1k
Tingting Fan China 25 919 1.2× 252 0.7× 113 0.5× 111 0.8× 251 1.8× 65 1.5k
Mohammad Gholami Iran 19 881 1.1× 539 1.5× 156 0.7× 127 0.9× 74 0.5× 47 1.5k
Stephanie M. Tortorella Australia 9 652 0.8× 360 1.0× 123 0.5× 133 0.9× 103 0.7× 12 1.1k
Donghang Xu China 17 449 0.6× 130 0.4× 226 1.0× 216 1.5× 104 0.7× 54 995
Qiyun Tang China 23 625 0.8× 366 1.0× 143 0.6× 102 0.7× 110 0.8× 65 1.3k
Gianluca Di Cara Italy 18 412 0.5× 210 0.6× 123 0.5× 74 0.5× 74 0.5× 26 770
Jagdish K. Jaiswal New Zealand 17 266 0.3× 143 0.4× 115 0.5× 120 0.8× 59 0.4× 39 903
Tomasz Cichoń Poland 19 698 0.9× 221 0.6× 209 0.9× 101 0.7× 348 2.4× 58 1.4k
Patricia García‐López Mexico 20 469 0.6× 137 0.4× 136 0.6× 135 0.9× 70 0.5× 54 1.1k
M Zadinová Czechia 19 521 0.7× 152 0.4× 125 0.6× 136 0.9× 62 0.4× 46 1.1k

Countries citing papers authored by Max Kullberg

Since Specialization
Citations

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

Fields of papers citing papers by Max Kullberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Max Kullberg

This figure shows the co-authorship network connecting the top 25 collaborators of Max Kullberg. A scholar is included among the top collaborators of Max Kullberg 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 Max Kullberg. Max Kullberg 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
2.
Mann, Kristine, et al.. (2018). Intratumoral delivery of antigen with complement C3-bound liposomes reduces tumor growth in mice. Nanomedicine Nanotechnology Biology and Medicine. 18. 326–335. 15 indexed citations
3.
Mann, Kristine, et al.. (2017). Complement C3-dependent uptake of targeted liposomes into human macrophages, B cells, dendritic cells, neutrophils, and MDSCs. International Journal of Nanomedicine. Volume 12. 5149–5161. 23 indexed citations
4.
Mann, Kristine & Max Kullberg. (2016). Trastuzumab-targeted gene delivery to Her2-overexpressing breast cancer cells. Cancer Gene Therapy. 23(7). 221–228. 11 indexed citations
5.
Kullberg, Max, Holly Martinson, Kristine Mann, & Thomas J. Anchordoquy. (2015). Complement C3 mediated targeting of liposomes to granulocytic myeloid derived suppressor cells. Nanomedicine Nanotechnology Biology and Medicine. 11(6). 1355–1363. 26 indexed citations
6.
Smyth, Tyson, Max Kullberg, Noeen Malik, et al.. (2014). Biodistribution and delivery efficiency of unmodified tumor-derived exosomes. Journal of Controlled Release. 199. 145–155. 600 indexed citations breakdown →
7.
Kullberg, Max, Ryan L. McCarthy, & Thomas J. Anchordoquy. (2014). Gene delivery to Her-2+ breast cancer cells using a two-component delivery system to achieve specificity. Nanomedicine Nanotechnology Biology and Medicine. 10(6). 1253–1262. 11 indexed citations
8.
Kullberg, Max, Ryan L. McCarthy, & Thomas J. Anchordoquy. (2013). Systemic tumor-specific gene delivery. Journal of Controlled Release. 172(3). 730–736. 39 indexed citations
9.
Betker, Jamie L., Max Kullberg, Joe Gomez, & Thomas J. Anchordoquy. (2013). Cholesterol Domains Enhance Transfection. Therapeutic Delivery. 4(4). 453–462. 21 indexed citations
10.
Kullberg, Max, et al.. (2013). Abstract P5-02-02: Specific gene delivery to Her-2+ breast cancer cells using immunoliposomes. Cancer Research. 73(24_Supplement). P5–2.
11.
Kullberg, Max, et al.. (2010). Listeriolysin O enhances cytoplasmic delivery by Her-2 targeting liposomes. Journal of drug targeting. 18(4). 313–320. 29 indexed citations
12.
Kullberg, Max, et al.. (2008). A two-component drug delivery system using Her-2-targeting thermosensitive liposomes. Journal of drug targeting. 17(2). 98–107. 25 indexed citations
13.
Kullberg, Max, et al.. (2004). Improved drug delivery to cancer cells: a method using magnetoliposomes that target epidermal growth factor receptors. Medical Hypotheses. 64(3). 468–470. 25 indexed citations
14.
Kullberg, Max, et al.. (1981). The analysis of arildone in plasma, urine and feces by gas—liquid chromatography with electron-capture detection. Journal of Chromatography B Biomedical Sciences and Applications. 222(2). 213–223. 6 indexed citations
15.
Brown, R. R., et al.. (1980). Analysis of mepivacaine, bupivacaine, etidocaine, lidocaine, and tetracaine. Journal of Pharmaceutical Sciences. 69(5). 603–605. 18 indexed citations
16.
Kullberg, Max, et al.. (1980). High-performance liquid chromatographic analysis of amrinone and its N-acetyl derivative in plasma. Journal of Chromatography A. 187(1). 264–270. 21 indexed citations
17.
Kullberg, Max, et al.. (1978). High-performance liquid chromatographic determination of plasma and urinary 1-ethyl-1,4-dihydro-4-oxo-1,8-naphthyridine -3,7-dicarboxylic acid. Journal of Chromatography A. 152(1). 145–152. 8 indexed citations
18.
Kullberg, Max & Charles W. Gorodetzky. (1974). Studies on the Use of XAD-2 Resin for Detection of Abused Drugs in Urine. Clinical Chemistry. 20(2). 177–183. 33 indexed citations
19.
Gorodetzky, Charles W. & Max Kullberg. (1974). Validity of screening methods for drugs of abuse in biological fluids; II. Heroin in plasma and saliva. Clinical Pharmacology & Therapeutics. 15(6). 579–587. 23 indexed citations
20.
Kullberg, Max, et al.. (1973). Studies on the quantitative extraction of morphine from urine using nonionic XAD-2 resin. Biochemical Medicine. 7(1). 145–158. 20 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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