Daniela Radl

426 citations
15 papers · 352 · h-index 11

Impact in

Papers in

Daniela Radl

15 papers receiving 343 citations

Peers

Daniela Radl
Comparison fields: 5 of 53
  • Endocrinology, Diabetes and Metabolism 148
  • Cellular and Molecular Neuroscience 93
  • Endocrine and Autonomic Systems 25
  • Reproductive Medicine 28
  • Biological Psychiatry 7
Replace Kirti Chaturvedi with:
Kirti Chaturvedi United States
Pierfrancesco Vargiu Spain
Jutta Gloddek Germany
B. M. Lewis United Kingdom
Yasuhiko Kanou Japan
Haruo Mizuta Japan
Yasutomi Kuroki Japan
Esteban Lavaque Spain
Tamás Csikós United States
S Stone United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniela Radl

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Radl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

15 of 15 papers shown
#Work
1 200945
2 201137
3 201736
4 200935
5 200835
6 201633
7 201332
8 202023
9 201021
10 201117
11 201111
12 201710
13 20119
14 20106
15 20252

About Daniela Radl

Daniela Radl is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Cellular and Molecular Neuroscience, Genetics and Immunology, having authored 15 papers that have together received 352 indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (5 papers), Receptor Mechanisms and Signaling (4 papers), Neurotransmitter Receptor Influence on Behavior (4 papers), Estrogen and related hormone effects (3 papers), Retinoids in leukemia and cellular processes (3 papers), Pituitary Gland Disorders and Treatments (3 papers), Cell death mechanisms and regulation (2 papers) and Neuroscience and Neuropharmacology Research (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (148 citations), Cellular and Molecular Neuroscience (93 citations), Endocrine and Autonomic Systems (25 citations), Reproductive Medicine (28 citations) and Biological Psychiatry (7 citations). Daniela Radl has collaborated with scholars based in Argentina, United States and Mexico. Frequent co-authors include Daniel Pisera, Adriana Seilicovich, Emiliana Borrelli, Jimena Ferraris, Gabriela Jaita, Verónica Zaldivar, Robert G. Lewis, Sandra Zárate, Martina Chiacchiaretta and Karen Brami‐Cherrier. Their work appears in journals such as Neuroendocrinology, Proceedings of the National Academy of Sciences, PLoS ONE, Journal of Neuroendocrinology and Frontiers of hormone research.

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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