Erika L. Pearce
- Immunology top 0.05%
- Molecular Biology top 0.5%
- Oncology top 0.2%
- Cancer Research top 0.2%
- Epidemiology top 0.5%
- Co-authors
- Edward J. PearceChih‐Hao ChangGerritje J. W. van der WindtDavid O’SullivanMichael D. BuckRussell G. JonesJonathan D. CurtisBart Everts
- Topics
- Immune Cell Function and Interaction (43 papers)T-cell and B-cell Immunology (23 papers)Immune cells in cancer (21 papers)
- Partner nations
- United StatesGermanyCanada
In The Last Decade
Erika L. Pearce
80 papers receiving 23.0k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Immunology 14.2k
- Molecular Biology 8.5k
- Oncology 4.9k
- Cancer Research 4.4k
- Epidemiology 2.8k
Countries citing papers authored by Erika L. Pearce
This map shows the geographic impact of Erika L. Pearce'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 Erika L. Pearce with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Erika L. Pearce more than expected).
Fields of papers citing papers by Erika L. Pearce
This network shows the impact of papers produced by Erika L. Pearce. 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 Erika L. Pearce. The network helps show where Erika L. Pearce may publish in the future.
Co-authorship network of co-authors of Erika L. Pearce
This figure shows the co-authorship network connecting the top 25 collaborators of Erika L. Pearce. A scholar is included among the top collaborators of Erika L. Pearce 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 Erika L. Pearce. Erika L. Pearce is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 7 | |
| 5 | 16 | |
| 6 | 86 | |
| 7 | 8 | |
| 8 | 46 | |
| 9 | 22 | |
| 10 | Mitochondrial Dynamics Controls T Cell Fate through Metabolic Programmingbreakdown → | 1041 |
| 11 | 254 | |
| 12 | The Colonic Crypt Protects Stem Cells from Microbiota-Derived Metabolitesbreakdown → | 534 |
| 13 | T cell metabolism drives immunitybreakdown → | 867 |
| 14 | Memory CD8+ T Cells Use Cell-Intrinsic Lipolysis to Support the Metabolic Programming Necessary for Developmentbreakdown → | 611 |
| 15 | 1 | |
| 16 | 236 | |
| 17 | 1 | |
| 18 | 192 | |
| 19 | Control of Effector CD8 + T Cell Function by the Transcription Factor Eomesoderminbreakdown → | 774 |
| 20 | 5 |
About Erika L. Pearce
Erika L. Pearce is a scholar working on Immunology, Biological Psychiatry and Physiology, having authored 83 papers that have together received 23.1k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (43 papers), T-cell and B-cell Immunology (23 papers) and Immune cells in cancer (21 papers). The work is most often cited by research in Immunology (14.2k citations), Cancer Research (4.4k citations) and Biological Psychiatry (482 citations). Erika L. Pearce has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include Edward J. Pearce, Chih‐Hao Chang, Gerritje J. W. van der Windt, David O’Sullivan, Michael D. Buck, Russell G. Jones, Jonathan D. Curtis, Bart Everts, Stanley Ching‐Cheng Huang and Jing Qiu. Their work appears in journals such as Nature, Science and Cell.
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.