Pamela A. Davol

706 citations
24 papers · 558 indexed · h-index 13

Pamela A. Davol

24 papers receiving 538 citations

Peers

Pamela A. Davol
Comparison fields: 5 of 52
  • Oncology 282
  • Immunology 196
  • Radiology, Nuclear Medicine and Imaging 195
  • Genetics 60
  • Biotechnology 29
Replace Ekkehard Moessner with:
Ekkehard Moessner Switzerland
Silvia Mele United Kingdom
Dipa Patel United States
Elínborg Ostermann Austria
Troy A. Luster United States
Fanny Bouquet France
Stefania Martignone Italy
Aaron M. LeBeau United States
W. H. Miller United States
Hillary J. Millar United States
Pamela A. Davol relative to Ekkehard Moessner Switzerland Ekkehard Moessner's profile →
Citations per field
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Ekkehard Moessner · 1×
Citations per year

Countries citing papers authored by Pamela A. Davol

Since Specialization
Citations

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

Fields of papers citing papers by Pamela A. Davol

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pamela A. Davol. 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 Pamela A. Davol. The network helps show where Pamela A. Davol may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 200823
2 200663
3 200625
4 200619
5 200674
6
Preclinical studies comparing different bispecific antibodies for redirecting T cell cytotoxicity to extracellular antigens on prostate carcinomas.
200514
7 200550
8 200519
9 20054
10 20042
11 200429
12 200424
13
Shc proteins are strong, independent prognostic markers for both node-negative and node-positive primary breast cancer.
200356
14 199924
15 19991
16 199911
17 19977
18 19961
19 19959
20 199510

About Pamela A. Davol

Pamela A. Davol is a scholar working on Oncology, Immunology and Genetics, having authored 24 papers that have together received 558 indexed citations. Recurring topics across this work include CAR-T cell therapy research (10 papers), Monoclonal and Polyclonal Antibodies Research (8 papers), Proteoglycans and glycosaminoglycans research (5 papers), Immunotherapy and Immune Responses (4 papers), HER2/EGFR in Cancer Research (4 papers), Toxin Mechanisms and Immunotoxins (4 papers), Fibroblast Growth Factor Research (3 papers) and Mesenchymal stem cell research (3 papers). The work is most often cited by research in Oncology (282 citations), Immunology (196 citations) and Radiology, Nuclear Medicine and Imaging (195 citations). Pamela A. Davol has collaborated with scholars based in United States, Poland and Canada. Frequent co-authors include Lawrence G. Lum, A. Raymond Frackelton, Jonathan M. Gall, Gerald J. Elfenbein, Randall J. Lee, Abby Maizel, Nicola Kouttab, James B. Davis, James F. Padbury and Wendy B. Young. Their work appears in journals such as Blood, Cancer and Clinical Cancer Research.

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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