Leonard E. Grosso

1.3k citations
45 papers · 1.0k · h-index 19

Impact in

Papers in

Leonard E. Grosso

45 papers receiving 1.0k citations

Peers

Leonard E. Grosso
Comparison fields: 5 of 94
  • Immunology and Allergy 92
  • Cancer Research 147
  • Microbiology 7
  • Oncology 250
  • Pathology and Forensic Medicine 164
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P Stosiek Germany
O. Kaufmann Germany
Tsuyoshi Tange Japan
Hitoshi Ohtani Japan
H. H. Peter Germany
Jürgen Galle Germany
Juliane K. Franz Germany
James R. Dasch United States
Katsunari Tezuka Japan
Dominique Hamel‐Teillac France
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Citations per field
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Citations per year

Countries citing papers authored by Leonard E. Grosso

Since Specialization
Citations

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

Fields of papers citing papers by Leonard E. Grosso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Transcriptional regulation of c-myc during chemically induced differentiation of HL-60 cultures.
1985110
2 199199
3 198468
4 200664
5 199157
6 199349
7
Expression of parathyroidlike protein in normal, proliferative, and neoplastic human breast tissues.
199349
8 199143
9 199339
10 199138
11 199336
12 199835
13 199333
14 200028
15 199320
16 200220
17
Chromatin structure of the c-myc gene in HL-60 cells during alterations of transcriptional activity.
198520
18 200119
19 199119
20 199915

About Leonard E. Grosso

Leonard E. Grosso is a scholar working on Pathology and Forensic Medicine, Oncology, Cancer Research, Molecular Biology and Genetics, having authored 45 papers that have together received 1.0k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (12 papers), Protease and Inhibitor Mechanisms (8 papers), Viral-associated cancers and disorders (7 papers), Cell Adhesion Molecules Research (7 papers), Connective tissue disorders research (7 papers), Polyomavirus and related diseases (6 papers), Salivary Gland Tumors Diagnosis and Treatment (5 papers) and Acute Myeloid Leukemia Research (4 papers). The work is most often cited by research in Immunology and Allergy (92 citations), Cancer Research (147 citations), Microbiology (7 citations), Oncology (250 citations) and Pathology and Forensic Medicine (164 citations). Leonard E. Grosso has collaborated with scholars based in United States, Spain and Belgium. Frequent co-authors include Henry C. Pitot, Robert P. Mecham, Cherie H. Dunphy, Eimear Cleary, L.B. Sandberg, Mark A. Gibson, Pyong Woo Park, Stephen A. Moser, Brian T. Collins and Rosa M. Dávila. Their work appears in journals such as Acta Cytologica, Diagnostic Cytopathology, Archives of Pathology & Laboratory Medicine, Biochemistry and Biochemical Journal.

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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