Emanuela Maderna

45 papers receiving 1.0k citations

Peers

Emanuela Maderna
Comparison fields: 5 of 100
  • Genetics 188
  • Neurology 114
  • Developmental Neuroscience 37
  • Oncology 218
  • Neurology 94
Replace Yuanqing Yan with:
Yuanqing Yan United States
Camelia‐Maria Monoranu Germany
Claus G. Haase Germany
Tomokazu Aoki Japan
Marta Segarra Germany
Omar Nyabi Belgium
Maddalena Ruggieri Italy
Elena Martínez‐Sáez Spain
Josefine Radke Germany
Huiming Xu China
Emanuela Maderna relative to Yuanqing Yan United States Yuanqing Yan's profile →
Citations per field
00.5×3.4×
Yuanqing Yan · 1×
Citations per year

Countries citing papers authored by Emanuela Maderna

Since Specialization
Citations

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

Fields of papers citing papers by Emanuela Maderna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014149
2 2012115
3 200977
4 200953
5 202051
6 200746
7 200944
8 201140
9 202134
10 200730
11 201629
12 200628
13 201224
14 201121
15 200821
16 201420
17 200819
18 201618
19 201717
20 201117

About Emanuela Maderna

Emanuela Maderna is a scholar working on Molecular Biology, Physiology, Neurology, Genetics and Oncology, having authored 47 papers that have together received 1.0k indexed citations. Recurring topics across this work include Alzheimer's disease research and treatments (8 papers), Glioma Diagnosis and Treatment (7 papers), Forensic Anthropology and Bioarchaeology Studies (6 papers), Brain Metastases and Treatment (4 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Dementia and Cognitive Impairment Research (4 papers), Paleopathology and ancient diseases (3 papers) and Neuroscience and Neuropharmacology Research (3 papers). The work is most often cited by research in Genetics (188 citations), Neurology (114 citations), Developmental Neuroscience (37 citations), Oncology (218 citations) and Neurology (94 citations). Emanuela Maderna has collaborated with scholars based in Italy, United Kingdom and United States. Frequent co-authors include Bianca Pollo, Andrea Salmaggi, Chiara Calatozzolo, Fabrizio Tagliavini, Gaetano Finocchiaro, Marcella Catania, Fabio Moda, Cristina Cattaneo, Antonio Silvani and J.-P. Brandel. Their work appears in journals such as Cancer Biology & Therapy, Brain Pathology, Journal of Neuro-Oncology, Neurological Sciences and Journal of Alzheimer s Disease.

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.

Explore authors with similar magnitude of impact