David Apelian

2.6k total citations · 1 hit paper
36 papers, 1.9k citations indexed

About

David Apelian is a scholar working on Hepatology, Oncology and Immunology. According to data from OpenAlex, David Apelian has authored 36 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Hepatology, 13 papers in Oncology and 11 papers in Immunology. Recurrent topics in David Apelian's work include Hepatitis C virus research (14 papers), Immunotherapy and Immune Responses (9 papers) and Cancer Research and Treatments (7 papers). David Apelian is often cited by papers focused on Hepatitis C virus research (14 papers), Immunotherapy and Immune Responses (9 papers) and Cancer Research and Treatments (7 papers). David Apelian collaborates with scholars based in United States, New Zealand and Netherlands. David Apelian's co-authors include Robert G. Gish, Zachary Goodman, Ting‐Tsung Chang, Anna S. Lok, Jin Liang Zhu, Adrián Gadano, Richard B. Wilber, Deborah DeHertogh, Anne Cross and Jose D. Sollano and has published in prestigious journals such as New England Journal of Medicine, Journal of Clinical Oncology and Genes & Development.

In The Last Decade

David Apelian

35 papers receiving 1.9k citations

Hit Papers

A Comparison of Entecavir and Lamivudine for HBeAg-Positi... 2006 2026 2012 2019 2006 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Apelian United States 16 1.3k 1.3k 343 315 253 36 1.9k
Barbara Testoni France 29 1.7k 1.3× 1.4k 1.1× 288 0.8× 279 0.9× 689 2.7× 77 2.3k
Hans Christian Spangenberg Germany 20 1.3k 1.0× 1.7k 1.3× 905 2.6× 266 0.8× 260 1.0× 42 2.5k
Hiroyuki Ohnuma Japan 17 547 0.4× 347 0.3× 134 0.4× 174 0.6× 252 1.0× 48 1.1k
Chu Chieh Hsia United States 19 784 0.6× 1.0k 0.8× 72 0.2× 328 1.0× 438 1.7× 27 1.6k
Noriyoshi Kuzushita Japan 21 563 0.4× 697 0.6× 521 1.5× 139 0.4× 200 0.8× 36 1.3k
B Ren China 13 1.9k 1.4× 1.4k 1.1× 263 0.8× 373 1.2× 570 2.3× 13 2.4k
Kiyoshi Mochizuki Japan 18 1.1k 0.9× 1.2k 0.9× 439 1.3× 195 0.6× 322 1.3× 44 1.9k
Patrick Soussan France 23 1.0k 0.8× 836 0.7× 191 0.6× 188 0.6× 381 1.5× 47 1.5k
Simona Schivazappa Italy 7 574 0.4× 550 0.4× 602 1.8× 278 0.9× 78 0.3× 9 1.1k
Anna Suk‐Fong Lok United States 17 1.1k 0.8× 1.1k 0.9× 106 0.3× 127 0.4× 119 0.5× 21 1.4k

Countries citing papers authored by David Apelian

Since Specialization
Citations

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

Fields of papers citing papers by David Apelian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Apelian

This figure shows the co-authorship network connecting the top 25 collaborators of David Apelian. A scholar is included among the top collaborators of David Apelian 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 David Apelian. David Apelian 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.
Muscarella, Peter, Tanios Bekaii‐Saab, Kristi McIntyre, et al.. (2021). A Phase 2 Randomized Placebo-Controlled Adjuvant Trial of GI-4000, a Recombinant Yeast Expressing Mutated RAS Proteins in Patients with Resected Pancreas Cancer. SHILAP Revista de lepidopterología. 7(1). 8–19. 17 indexed citations
4.
Gane, Edward, Christian Schwabe, Catherine Stedman, et al.. (2015). LP27 : ACH-3422, A novel nucleotide prodrug inhibitor of HCV NS5B polymerase. Journal of Hepatology. 62. S277–S277. 3 indexed citations
5.
Chaft, Jamie E., Anya M. Litvak, Maria E. Arcila, et al.. (2014). Phase II Study of the GI-4000 KRAS Vaccine After Curative Therapy in Patients With Stage I-III Lung Adenocarcinoma Harboring a KRAS G12C, G12D, or G12V Mutation. Clinical Lung Cancer. 15(6). 405–410. 64 indexed citations
6.
Gaggar, Anuj, Claire Coeshott, David Apelian, et al.. (2014). Safety, tolerability and immunogenicity of GS-4774, a hepatitis B virus-specific therapeutic vaccine, in healthy subjects: A randomized study. Vaccine. 32(39). 4925–4931. 80 indexed citations
7.
8.
Ardiani, Andressa, Benedetto Farsaci, Connie J. Rogers, et al.. (2013). Combination Therapy with a Second-Generation Androgen Receptor Antagonist and a Metastasis Vaccine Improves Survival in a Spontaneous Prostate Cancer Model. Clinical Cancer Research. 19(22). 6205–6218. 71 indexed citations
9.
Bilušić, Marijo, Christopher R. Heery, Philip M. Arlen, et al.. (2013). Phase I trial of a recombinant yeast-CEA vaccine (GI-6207) in adults with metastatic CEA-expressing carcinoma. Cancer Immunology Immunotherapy. 63(3). 225–234. 78 indexed citations
12.
Gameiro, Sofia R., et al.. (2011). Exploitation of differential homeostatic proliferation of T-cell subsets following chemotherapy to enhance the efficacy of vaccine-mediated antitumor responses. Cancer Immunology Immunotherapy. 60(9). 1227–1242. 57 indexed citations
13.
D’Angelo, Sandra P., Lee M. Krug, Corey J. Crevar, et al.. (2011). Immunogenicity of GI-4000 vaccine in adjuvant consolidation therapy following definitive treatment in patients with stage I-III adenocarcinoma of the lung with G12C, G12D, or G12V KRAS mutations.. Journal of Clinical Oncology. 29(15_suppl). 7070–7070. 4 indexed citations
14.
Madan, Ravi A., Marijo Bilušić, James W. Hodge, et al.. (2011). A phase I trial of a yeast-based therapeutic cancer vaccine targeting CEA.. Journal of Clinical Oncology. 29(15_suppl). 2604–2604. 3 indexed citations
15.
Dai, Shaodong, Sarah Oakes, Richard C. Duke, et al.. (2010). Mutation-specific control of BCR-ABL T315I positive leukemia with a recombinant yeast-based therapeutic vaccine in a murine model. Vaccine. 28(37). 6028–6035. 14 indexed citations
16.
McHutchison, John G., Gregory T. Everson, Ira M. Jacobson, et al.. (2010). 277 GI-5005 THERAPEUTIC VACCINE PLUS PEG-IFN/RIBAVIRIN IMPROVES BIOPSY NECRO-INFLAMMATORY SCORES AND ALT NORMALIZATION AT 48 WEEKS VERSUS PEG-IFN/RIBAVIRIN IN GENOTYPE 1 CHRONIC HCV PATIENTS. Journal of Hepatology. 52. S116–S116. 3 indexed citations
17.
Guo, Zhimin, Yingnian Lu, Sarah Oakes, et al.. (2008). Trans-national patterns of pancreas cancer ras mutations and discovery of a new ras mutation with oncogenic synergy when found with ras codon 12 mutations. Clinical Cancer Research. 14. 1 indexed citations
18.
Duke, Richard C., et al.. (2007). Control of leukemia driven by T315I escape mutations in BCR-ABL with yeast-based Tarmogen immunotherapy. Molecular Cancer Therapeutics. 6. 2 indexed citations
19.
Chang, Ting‐Tsung, Robert G. Gish, Robert de Man, et al.. (2006). A Comparison of Entecavir and Lamivudine for HBeAg-Positive Chronic Hepatitis B. New England Journal of Medicine. 354(10). 1001–1010. 1064 indexed citations breakdown →
20.
Haller, Aurelia A., Georg M. Lauer, Thomas H. King, et al.. (2006). Whole recombinant yeast-based immunotherapy induces potent T cell responses targeting HCV NS3 and Core proteins. Vaccine. 25(8). 1452–1463. 92 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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