Emily Pace
Impact in
- Oncology top 10%
- HER2/EGFR in Cancer Research
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- Monoclonal and Polyclonal Antibodies Research
Papers in
-
- PI3K/AKT/mTOR signaling in cancer 2
- Glycosylation and Glycoproteins Research 1
- Protein Degradation and Inhibitors 1
- Histone Deacetylase Inhibitors Research 1
- Oncology 6
- HER2/EGFR in Cancer Research 4
- Co-authors
- Ulrik B. Nielsen (4 shared papers)Matthew Onsum (2 shared papers)Birgit Schoeberl (5 shared papers)Lin Nie (2 shared papers)Jeffrey A. Engelman (1 shared paper)Anthony C. Faber (1 shared paper)Danan Li (1 shared paper)Kwok‐Kin Wong (1 shared paper)
- Journals
- Cancer Research (3 papers)Blood (1 paper)Journal of Clinical Oncology (1 paper)npj Systems Biology and Applications (1 paper)Molecular Cancer Therapeutics (1 paper)
- Partner nations
- United StatesGermanySwitzerland
In The Last Decade
Emily Pace
8 papers receiving 349 citations
Peers
Comparison fields: 5 of 44
- Oncology 210
- Radiology, Nuclear Medicine and Imaging 126
- Modeling and Simulation 16
- Molecular Biology 197
- Computational Theory and Mathematics 39
Countries citing papers authored by Emily Pace
This map shows the geographic impact of Emily Pace'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 Emily Pace with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emily Pace more than expected).
Fields of papers citing papers by Emily Pace
This network shows the impact of papers produced by Emily Pace. 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 Emily Pace. The network helps show where Emily Pace may publish in the future.
Co-authors
The 25 scholars most cited alongside Emily Pace, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 215 | |
| 2 | 2013 | 85 | |
| 3 | 2017 | 33 | |
| 4 | 2021 | 7 | |
| 5 | 2006 | 7 | |
| 6 | 2015 | 4 | |
| 7 | 2013 | 2 | |
| 8 | 2013 | 1 | |
| 9 | 2012 | 0 |
About Emily Pace
Emily Pace is a scholar working on Molecular Biology, Oncology, Computational Theory and Mathematics, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 9 papers that have together received 354 indexed citations. Recurring topics across this work include HER2/EGFR in Cancer Research (4 papers), Computational Drug Discovery Methods (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), PI3K/AKT/mTOR signaling in cancer (2 papers), Acute Myeloid Leukemia Research (1 paper), Glycosylation and Glycoproteins Research (1 paper), Protein Degradation and Inhibitors (1 paper) and Histone Deacetylase Inhibitors Research (1 paper). The work is most often cited by research in Oncology (210 citations), Radiology, Nuclear Medicine and Imaging (126 citations), Modeling and Simulation (16 citations), Molecular Biology (197 citations) and Computational Theory and Mathematics (39 citations). Emily Pace has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Ulrik B. Nielsen, Matthew Onsum, Birgit Schoeberl, Lin Nie, Jeffrey A. Engelman, Anthony C. Faber, Danan Li, Kwok‐Kin Wong, Olga Burenkova and Katherine Crosby. Their work appears in journals such as Cancer Research, Blood, Journal of Clinical Oncology, npj Systems Biology and Applications and Molecular Cancer Therapeutics.
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.