Denise E. Kirschner

167 papers receiving 11.1k citations

Denise E. Kirschner's Hit Papers

A methodology for performing global uncertainty and sensitivity analysis in systems biology 2008 · 2.2k citations
2.2k0+11+22Years since publication50010001.5k2.0k

Peers

Denise E. Kirschner
Comparison fields: 5 of 200
  • Modeling and Simulation 2.5k
  • Virology 1.2k
  • Infectious Diseases 3.7k
  • Immunology 2.7k
  • Public Health, Environmental and Occupational Health 2.8k
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Countries citing papers authored by Denise E. Kirschner

Since Specialization
Citations

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

Fields of papers citing papers by Denise E. Kirschner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Denise E. Kirschner. 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 Denise E. Kirschner. The network helps show where Denise E. Kirschner may publish in the future.

Co-authors

The 25 scholars most cited alongside Denise E. Kirschner, 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 Denise E. Kirschner Line = papers co-authored together Denise E. Kirschner links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 170 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A methodology for performing global uncertainty and sensitivity analysis in systems biology
Hit paper breakdown →
20082153
2
Dynamics of HIV infection of CD4+ T cells
Hit paper breakdown →
1993744
3
Modeling immunotherapy of the tumor - immune interaction
Hit paper breakdown →
1998694
4 1997389
5 2013262
6 2015246
7 2018245
8 2004237
9 2002196
10 2001185
11 2007179
12 2014142
13 2011131
14 2004128
15 2004124
16 2009124
17 2006122
18
Using Mathematics to Understand HIV Immune Dynamics
1997117
19 2008111
20 1996111

About Denise E. Kirschner

Denise E. Kirschner is a scholar working on Infectious Diseases, Epidemiology, Immunology, Molecular Biology and Virology, having authored 170 papers that have together received 11.5k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (79 papers), Mycobacterium research and diagnosis (42 papers), HIV Research and Treatment (29 papers), Immune Cell Function and Interaction (28 papers), T-cell and B-cell Immunology (19 papers), vaccines and immunoinformatics approaches (18 papers), Mathematical and Theoretical Epidemiology and Ecology Models (15 papers) and Evolution and Genetic Dynamics (15 papers). The work is most often cited by research in Modeling and Simulation (2.5k citations), Virology (1.2k citations), Infectious Diseases (3.7k citations), Immunology (2.7k citations) and Public Health, Environmental and Occupational Health (2.8k citations). Denise E. Kirschner has collaborated with scholars based in United States, France and Italy. Frequent co-authors include Simeone Marino, Ian B. Hogue, Jennifer J. Linderman, John C. Panetta, JoAnne L. Flynn, Alan S. Perelson, Rob J. de Boer, Glenn F. Webb, Martin J. Blaser and Suzanne Lenhart. Their work appears in journals such as Journal of Theoretical Biology, The Journal of Immunology, PLoS Computational Biology, Bulletin of Mathematical Biology and JAIDS Journal of Acquired Immune Deficiency Syndromes.

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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