Kimberly E. Foreman

4.8k citations
56 papers · 3.8k indexed · h-index 29

Kimberly E. Foreman

56 papers receiving 3.8k citations

Peers

Kimberly E. Foreman
Comparison fields: 5 of 116
  • Oncology 1.7k
  • Cancer Research 738
  • Immunology and Allergy 207
  • Immunology 681
  • Molecular Biology 1.8k
Replace Cecilia Sgadari with:
Cecilia Sgadari Italy
William Damsky United States
Elizabeth Hyjek United States
Hartmut Merz Germany
Yoshio Endo Japan
Paul G. Murray United Kingdom
Yasuharu Nishimura Japan
Christina Addison Canada
Michèle Grieco Italy
Martin Oft United States
Kimberly E. Foreman relative to Cecilia Sgadari Italy Cecilia Sgadari's profile →
Citations per field
00.5×1.5×2.4×
Cecilia Sgadari · 1×
Citations per year

Countries citing papers authored by Kimberly E. Foreman

Since Specialization
Citations

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

Fields of papers citing papers by Kimberly E. Foreman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 2016138
2 2015142
3 201171
4
Inhibition of Notch signaling reduces the stem-like population of breast cancer cells and prevents mammosphere formation.
2010119
5 2008309
6 200681
7 20037
8 200336
9 200261
10 20028
11 200125
12 199914
13 199827
14
Comparison of HHV-8 derived from Kaposis sarcoma and body cavity based lymphoma
19973
15 199710
16 199749
17 1997139
18 199610
19 199597
20 1994393

About Kimberly E. Foreman

Kimberly E. Foreman is a scholar working on Oncology, Immunology and Allergy, Virology, Infectious Diseases and Immunology, having authored 56 papers that have together received 3.8k indexed citations. Recurring topics across this work include Viral-associated cancers and disorders (18 papers), Cytomegalovirus and herpesvirus research (13 papers), Parvovirus B19 Infection Studies (9 papers), Developmental Biology and Gene Regulation (6 papers), Extracellular vesicles in disease (5 papers), Cell Adhesion Molecules Research (5 papers), Histiocytic Disorders and Treatments (4 papers) and Complement system in diseases (4 papers). The work is most often cited by research in Oncology (1.7k citations), Cancer Research (738 citations), Immunology and Allergy (207 citations), Immunology (681 citations) and Molecular Biology (1.8k citations). Kimberly E. Foreman has collaborated with scholars based in United States, Japan and Taiwan. Frequent co-authors include Lucio Miele, Brian J. Nickoloff, Todd E. Golde, Gopal N. Gupta, Clodia Osipo, Paola Rizzo, Paul C. Kuo, Carrie A. Franzen, Peter A. Ward and Christine L. Curry. Their work appears in journals such as The Journal of Urology, Archives of Pathology & Laboratory Medicine, Journal of Dermatological Science, Journal of Virology and Journal of Clinical Investigation.

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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