Debora Macis

1.4k citations
49 papers · 908 · h-index 17

Impact in

Papers in

    • Cancer Risks and Factors 12
    • Estrogen and related hormone effects 13
    • BRCA gene mutations in cancer 4

Debora Macis

47 papers receiving 885 citations

Peers

Debora Macis
Comparison fields: 5 of 81
  • Cancer Research 171
  • Reproductive Medicine 83
  • Oncology 222
  • Genetics 171
  • Pharmacology 52
Replace Arnaldo Capelli with:
Arnaldo Capelli Italy
Zora Lasabová Slovakia
Teguh Aryandono Indonesia
Kazuo Tajima Japan
Urmila Chandran United States
Álvaro Cerda Brazil
Li Zhong China
Ningning Zhang China
Qiu Du China
Debora Macis relative to Arnaldo Capelli Italy Arnaldo Capelli's profile →
Citations per field
00.5×4.6×
Arnaldo Capelli · 1×
Citations per year

Countries citing papers authored by Debora Macis

Since Specialization
Citations

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

Fields of papers citing papers by Debora Macis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200485
2 201480
3 201766
4 201464
5 201159
6 200755
7 201055
8 200754
9 201150
10 200831
11 200329
12 200424
13 201322
14 201621
15 200920
16 201318
17 202316
18 202116
19 202115
20 201612

About Debora Macis

Debora Macis is a scholar working on Oncology, Genetics, Molecular Biology, Cancer Research and Pathology and Forensic Medicine, having authored 49 papers that have together received 908 indexed citations. Recurring topics across this work include Estrogen and related hormone effects (13 papers), Cancer Risks and Factors (12 papers), Metabolism, Diabetes, and Cancer (5 papers), Adipokines, Inflammation, and Metabolic Diseases (5 papers), BRCA gene mutations in cancer (4 papers), Breast Cancer Treatment Studies (4 papers), Pharmacogenetics and Drug Metabolism (4 papers) and Inflammatory mediators and NSAID effects (3 papers). The work is most often cited by research in Cancer Research (171 citations), Reproductive Medicine (83 citations), Oncology (222 citations), Genetics (171 citations) and Pharmacology (52 citations). Debora Macis has collaborated with scholars based in Italy, United Kingdom and Norway. Frequent co-authors include Aliana Guerrieri‐Gonzaga, Sara Gandini, Bernardo Bonanni, Harriet Johansson, Andrea DeCensi, Davide Serrano, S. Chigioni, G.C. Luvoni, Matteo Lazzeroni and Massimiliano Cazzaniga. Their work appears in journals such as Breast Cancer Research and Treatment, Cancer Research, Journal of Clinical Oncology, Cancer Prevention Research and Nutrients.

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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