Jesse D. Bloom

30.1k citations
148 papers · 13.1k indexed · 14 hit papers · h-index 57

Jesse D. Bloom

145 papers receiving 13.0k citations

Hit Papers

A pseudovi...8520052026201220192505007501000

Peers

Jesse D. Bloom
Comparison fields: 5 of 147
  • Infectious Diseases 5.7k
  • Molecular Biology 6.9k
  • Modeling and Simulation 448
  • Virology 429
  • Animal Science and Zoology 910
Replace Matthew Cotten with:
Matthew Cotten United Kingdom
David Veesler United States
Gary R. Whittaker United States
Sina Bavari United States
Deyin Guo China
Jinghua Yan China
Jason Greenbaum United States
Frank J. M. van Kuppeveld Netherlands
F.A. Rey France
Yi Shi China
Jesse D. Bloom relative to Matthew Cotten United Kingdom Matthew Cotten's profile →
Citations per field
00.5×7.3×
Matthew Cotten · 1×
Citations per year

Countries citing papers authored by Jesse D. Bloom

Since Specialization
Citations

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

Fields of papers citing papers by Jesse D. Bloom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jesse D. Bloom. 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 Jesse D. Bloom. The network helps show where Jesse D. Bloom may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jesse D. Bloom, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jesse D. Bloom Line = papers co-authored together Jesse D. Bloom links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20253
3 20251
4 20251
5 20239
6 20237
7 202219
8 202210
9 202273
10 202132
11
Prospective mapping of viral mutations that escape antibodies used to treat COVID-19breakdown →
2021448
12 202124
13 2020152
14 202038
15 2018117
16 201813
17
Permissive Secondary Mutations Enable the Evolution of Influenza Oseltamivir Resistancebreakdown →
2010511
18
Protein stability promotes evolvabilitybreakdown →
2006913
19
Why highly expressed proteins evolve slowlybreakdown →
2005610
20 2005271

About Jesse D. Bloom

Jesse D. Bloom is a scholar working on Virology, Infectious Diseases and Epidemiology, having authored 148 papers that have together received 13.1k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (48 papers), SARS-CoV-2 and COVID-19 Research (44 papers), RNA and protein synthesis mechanisms (27 papers), Respiratory viral infections research (26 papers), vaccines and immunoinformatics approaches (23 papers), Monoclonal and Polyclonal Antibodies Research (17 papers), Evolution and Genetic Dynamics (17 papers) and Protein Structure and Dynamics (15 papers). The work is most often cited by research in Infectious Diseases (5.7k citations), Molecular Biology (6.9k citations) and Modeling and Simulation (448 citations). Jesse D. Bloom has collaborated with scholars based in United States, South Africa and United Kingdom. Frequent co-authors include Frances H. Arnold, Allison J. Greaney, Tyler N. Starr, Adam S. Dingens, Katharine H. D. Crawford, Christopher R. Otey, Claus O. Wilke, D. Allan Drummond, Christoph Adami and David Baltimore. Their work appears in journals such as eLife, Journal of Virology, PLoS Pathogens, Virus Evolution and Viruses.

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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