Daniel Sellers

1.7k total citations · 1 hit paper
7 papers, 514 citations indexed

About

Daniel Sellers is a scholar working on Infectious Diseases, Molecular Biology and Health. According to data from OpenAlex, Daniel Sellers has authored 7 papers receiving a total of 514 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Infectious Diseases, 3 papers in Molecular Biology and 2 papers in Health. Recurrent topics in Daniel Sellers's work include SARS-CoV-2 and COVID-19 Research (3 papers), COVID-19 Clinical Research Studies (3 papers) and Tuberculosis Research and Epidemiology (2 papers). Daniel Sellers is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (3 papers), COVID-19 Clinical Research Studies (3 papers) and Tuberculosis Research and Epidemiology (2 papers). Daniel Sellers collaborates with scholars based in United States, Netherlands and Israel. Daniel Sellers's co-authors include Jingyou Yu, Dan H. Barouch, Jinyan Liu, Katherine McMahan, Abishek Chandrashekar, Catherine Jacob-Dolan, Ai‐ris Y. Collier, Julia Barrett, Michelle A. Lifton and Cindy Wu and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Daniel Sellers

7 papers receiving 506 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Vaccines elicit highly conserved cellular immunity to SARS-CoV-2 Omicron

2022 270 citations Jinyan Liu, Abishek Chandrashekar et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Sellers United States	5	301	152	83	63	50	7	514
Lindsey R. Robinson‐McCarthy United States	6	398 1.3×	151 1.0×	72 0.9×	15 0.2×	33 0.7×	12	484
Chris Ruis United Kingdom	2	486 1.6×	187 1.2×	30 0.4×	38 0.6×	59 1.2×	3	582
Saathvik R. Kannan United States	5	310 1.0×	136 0.9×	27 0.3×	20 0.3×	24 0.5×	7	400
Daniel Maloney United Kingdom	6	521 1.7×	213 1.4×	20 0.2×	51 0.8×	69 1.4×	11	626
Baisheng Li China	15	147 0.5×	167 1.1×	111 1.3×	52 0.8×	35 0.7×	59	525
Michelle N. Vu United States	8	354 1.2×	142 0.9×	76 0.9×	12 0.2×	26 0.5×	14	471
Shaofeng Deng China	10	360 1.2×	100 0.7×	65 0.8×	13 0.2×	24 0.5×	21	501
Emily Scher United Kingdom	3	488 1.6×	194 1.3×	15 0.2×	40 0.6×	59 1.2×	6	570
Kun Cai China	13	278 0.9×	174 1.1×	46 0.6×	60 1.0×	6 0.1×	44	533
Christopher L. D. McMillan Australia	11	204 0.7×	134 0.9×	83 1.0×	24 0.4×	12 0.2×	20	380

Countries citing papers authored by Daniel Sellers

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Sellers

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Sellers

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

All Works

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7 of 7 papers shown

1.

Vidal, Samuel J., Ninaad Lasrado, Lisa H. Tostanoski, et al.. (2025). Mining the CD4 antigen repertoire for next-generation tuberculosis vaccines. Cell. 188(24). 6791–6803.e13. 1 indexed citations

2.

Vidal, Samuel J., Daniel Sellers, Jingyou Yu, et al.. (2023). Attenuated Mycobacterium tuberculosis vaccine protection in a low-dose murine challenge model. iScience. 26(6). 106963–106963. 7 indexed citations

3.

Krishna, Naveen B., et al.. (2023). Towards universal synthetic heterotrophy using a metabolic coordinator. Metabolic Engineering. 79. 14–26. 4 indexed citations

4.

Collier, Ai‐ris Y., Catherine Brown, Katherine McMahan, et al.. (2022). Characterization of immune responses in fully vaccinated individuals after breakthrough infection with the SARS-CoV-2 delta variant. Science Translational Medicine. 14(641). eabn6150–eabn6150. 43 indexed citations

5.

Liu, Jinyan, Abishek Chandrashekar, Daniel Sellers, et al.. (2022). Vaccines elicit highly conserved cellular immunity to SARS-CoV-2 Omicron. Nature. 603(7901). 493–496. 270 indexed citations breakdown →

6.

Nkolola, Joseph P., Jingyou Yu, Huahua Wan, et al.. (2022). A bivalent SARS-CoV-2 monoclonal antibody combination does not affect the immunogenicity of a vector-based COVID-19 vaccine in macaques. Science Translational Medicine. 14(665). eabo6160–eabo6160. 4 indexed citations

7.

Kehe, Jared, Anthony Kulesa, Anthony Ortiz Lopez, et al.. (2019). Massively parallel screening of synthetic microbial communities. Proceedings of the National Academy of Sciences. 116(26). 12804–12809. 185 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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