Eva Surmacz

4.7k citations
64 papers · 3.9k · h-index 35

Impact in

Papers in

Eva Surmacz

64 papers receiving 3.8k citations

Peers

Eva Surmacz
Comparison fields: 5 of 100
  • Endocrine and Autonomic Systems 923
  • Cancer Research 907
  • Endocrinology, Diabetes and Metabolism 546
  • Oncology 840
  • Epidemiology 940
Replace Mariusz Koda with:
Mariusz Koda Poland
Donald P. Cameron Australia
Margaret C. Eggo United Kingdom
Jaap G. Neels France
Reid Huber United States
Sophie Vaulont France
Martin G. Sirois Canada
Carine Chavey France
Régine Merval France
Dennis Bruemmer United States
Eva Surmacz relative to Mariusz Koda Poland Mariusz Koda's profile →
Citations per field
00.5×4.3×
Mariusz Koda · 1×
Citations per year

Countries citing papers authored by Eva Surmacz

Since Specialization
Citations

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

Fields of papers citing papers by Eva Surmacz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 64 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2005492
2 2006315
3 2007193
4 2010190
5 2000183
6 2011154
7 2004122
8 2003117
9 2011106
10 200895
11 200794
12 200794
13 200587
14 200273
15 200472
16 201362
17 201061
18
Role of estrogen receptor alpha in modulating IGF-I receptor signaling and function in breast cancer.
200461
19 200160
20 200859

About Eva Surmacz

Eva Surmacz is a scholar working on Molecular Biology, Endocrine and Autonomic Systems, Genetics, Endocrinology, Diabetes and Metabolism and Oncology, having authored 64 papers that have together received 3.9k indexed citations. Recurring topics across this work include Regulation of Appetite and Obesity (23 papers), Growth Hormone and Insulin-like Growth Factors (12 papers), Estrogen and related hormone effects (11 papers), Adipose Tissue and Metabolism (9 papers), Adipokines, Inflammation, and Metabolic Diseases (9 papers), Metabolism, Diabetes, and Cancer (8 papers), Biochemical Analysis and Sensing Techniques (7 papers) and Cancer-related molecular mechanisms research (7 papers). The work is most often cited by research in Endocrine and Autonomic Systems (923 citations), Cancer Research (907 citations), Endocrinology, Diabetes and Metabolism (546 citations), Oncology (840 citations) and Epidemiology (940 citations). Eva Surmacz has collaborated with scholars based in United States, Italy and Hungary. Frequent co-authors include Cecilia Garofalo, Sandra Cascio, Antonio Russo, Rita Ferla, Mariusz Koda, S Sułkowski, M Sulkowska, Diego Sisci, László Ötvös and Monica Bartucci. Their work appears in journals such as Journal of Cellular Physiology, Annals of Oncology, Oncogene, Breast Cancer Research and Treatment and BMC Cancer.

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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