Daniel Marrama

4.3k total citations · 1 hit paper
6 papers, 2.3k citations indexed

About

Daniel Marrama is a scholar working on Molecular Biology, Infectious Diseases and Immunology. According to data from OpenAlex, Daniel Marrama has authored 6 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Infectious Diseases and 2 papers in Immunology. Recurrent topics in Daniel Marrama's work include vaccines and immunoinformatics approaches (5 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Viral Infections and Immunology Research (1 paper). Daniel Marrama is often cited by papers focused on vaccines and immunoinformatics approaches (5 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Viral Infections and Immunology Research (1 paper). Daniel Marrama collaborates with scholars based in United States, Denmark and Australia. Daniel Marrama's co-authors include Alessandro Sette, Bjoern Peters, Jason Greenbaum, April Frazier, Aaron Sutherland, Sydney I. Ramirez, Carolyn Rydyznski Moderbacher, Alba Grifoni, Lakshmanane Premkumar and Florian Krammer and has published in prestigious journals such as Cell, Nucleic Acids Research and Circulation Research.

In The Last Decade

Daniel Marrama

6 papers receiving 2.3k 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.

Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals

2020 2.2k citations Alba Grifoni, Daniela Weiskopf et al. Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Marrama United States	6	2.0k	537	512	465	238	6	2.3k
Aaron Sutherland United States	8	2.0k 1.0×	545 1.0×	524 1.0×	467 1.0×	242 1.0×	14	2.4k
Sydney I. Ramirez United States	9	2.3k 1.1×	572 1.1×	524 1.0×	549 1.2×	249 1.0×	12	2.6k
Carolyn Rydyznski Moderbacher United States	5	2.5k 1.2×	695 1.3×	567 1.1×	581 1.2×	273 1.1×	5	2.8k
C Tham Singapore	12	1.7k 0.9×	501 0.9×	396 0.8×	409 0.9×	190 0.8×	18	2.1k
José Mateus United States	12	2.5k 1.3×	736 1.4×	583 1.1×	605 1.3×	286 1.2×	20	3.0k
Kamini Kunasegaran Singapore	11	1.6k 0.8×	504 0.9×	379 0.7×	427 0.9×	179 0.8×	17	2.1k
Jared Feldman United States	13	2.2k 1.1×	419 0.8×	247 0.5×	702 1.5×	191 0.8×	24	2.6k
Evan C. Lam United States	14	2.1k 1.0×	351 0.7×	220 0.4×	558 1.2×	219 0.9×	23	2.4k
Neta S. Zuckerman Israel	20	1.2k 0.6×	332 0.6×	176 0.3×	389 0.8×	202 0.8×	73	2.0k
Meiyin Lin Singapore	4	1.1k 0.5×	307 0.6×	263 0.5×	263 0.6×	141 0.6×	6	1.3k

Countries citing papers authored by Daniel Marrama

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Marrama

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Marrama

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

All Works

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6 of 6 papers shown

1.

Kim, Kevin, Brendan Ha, Jason W. Bennett, et al.. (2024). Next-generation IEDB tools: a platform for epitope prediction and analysis. Nucleic Acids Research. 52(W1). W526–W532. 16 indexed citations

2.

Antunes, Ricardo da Silva, Lorenzo Quiambao, Sandeep Kumar Dhanda, et al.. (2023). T cell reactivity to Bordetella pertussis is highly diverse regardless of childhood vaccination. Cell Host & Microbe. 31(8). 1404–1416.e4. 9 indexed citations

3.

Marrama, Daniel, William D. Chronister, Randi Vita, et al.. (2023). PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins. BMC Bioinformatics. 24(1). 485–485. 5 indexed citations

4.

Roy, Payel, John Sidney, Cecilia S. Lindestam Arlehamn, et al.. (2022). Immunodominant MHC-II (Major Histocompatibility Complex II) Restricted Epitopes in Human Apolipoprotein B. Circulation Research. 131(3). 258–276. 12 indexed citations

5.

Marrama, Daniel, Jarjapu Mahita, Alessandro Sette, & Bjoern Peters. (2022). Lack of evidence of significant homology of SARS-CoV-2 spike sequences to myocarditis-associated antigens. EBioMedicine. 75. 103807–103807. 17 indexed citations

6.

Grifoni, Alba, Daniela Weiskopf, Sydney I. Ramirez, et al.. (2020). Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals. Cell. 181(7). 1489–1501.e15. 2241 indexed citations breakdown →

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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