Ewa Surmacz

1.7k citations
30 papers · 1.5k · h-index 20

Impact in

Papers in

Ewa Surmacz

30 papers receiving 1.5k citations

Peers

Ewa Surmacz
Comparison fields: 5 of 92
  • Endocrinology, Diabetes and Metabolism 657
  • Cancer Research 226
  • Oncology 377
  • Molecular Biology 1.0k
  • Genetics 337
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Regina Raz United States
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Anna Coppa Italy
Cong S. Zong United States
Akira Inomata Japan
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Gilbert J. Pommier France
Maki Moritani Japan
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Citations per field
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Citations per year

Countries citing papers authored by Ewa Surmacz

Since Specialization
Citations

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

Fields of papers citing papers by Ewa Surmacz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ewa Surmacz. 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 Ewa Surmacz. The network helps show where Ewa Surmacz may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Differential insulin-like growth factor I receptor signaling and function in estrogen receptor (ER)-positive MCF-7 and ER-negative MDA-MB-231 breast cancer cells.
2001153
2
Tamoxifen interferes with the insulin-like growth factor I receptor (IGF-IR) signaling pathway in breast cancer cells.
1997124
3 1997122
4 1982114
5 1995105
6 199881
7
Transforming potential of the insulin receptor substrate 1.
199580
8 199579
9
Overexpression of insulin receptor substrate 1 (IRS-1) in the human breast cancer cell line MCF-7 induces loss of estrogen requirements for growth and transformation.
199570
10 199970
11 199565
12 199765
13 199958
14 198250
15 200441
16 199239
17 198733
18
Cyclin D1 messenger RNA is inducible by platelet-derived growth factor in cultured fibroblasts.
199232
19 199823
20 199221

About Ewa Surmacz

Ewa Surmacz is a scholar working on Endocrinology, Diabetes and Metabolism, Genetics, Molecular Biology, Oncology and Surgery, having authored 30 papers that have together received 1.5k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (15 papers), Estrogen and related hormone effects (8 papers), Metabolism, Diabetes, and Cancer (8 papers), Pancreatic function and diabetes (4 papers), Animal Genetics and Reproduction (3 papers), Diabetes and associated disorders (3 papers), RNA Interference and Gene Delivery (3 papers) and Cancer-related Molecular Pathways (3 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (657 citations), Cancer Research (226 citations), Oncology (377 citations), Molecular Biology (1.0k citations) and Genetics (337 citations). Ewa Surmacz has collaborated with scholars based in United States, Poland and Italy. Frequent co-authors include Marina A. Guvakova, Renato Baserga, Jean‐Luc Burgaud, Loredana Mauro, Sebastiano Andò, Catia Morelli, Monica Bartucci, Consuelo D'Ambrosio, Masahiko Miura and Ricky R. Hirschhorn. Their work appears in journals such as Molecular and Cellular Biology, Experimental Cell Research, International Journal of Cancer, Biochemical and Biophysical Research Communications and Annals of the New York Academy of Sciences.

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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