Fernando L‐López

22 papers receiving 447 citations

Peers

Fernando L‐López
Comparison fields: 5 of 56
  • Cancer Research 132
  • Endocrine and Autonomic Systems 34
  • Endocrinology, Diabetes and Metabolism 73
  • Molecular Biology 276
  • Epidemiology 110
Replace Sergio Pedraza‐Arévalo with:
Sergio Pedraza‐Arévalo Spain
Antonio C. Fuentes-Fayos Spain
Ilaria Grossi Italy
Esther Rivero‐Cortés Spain
Stéphanie Lacomme France
P Mora Germany
Joanna Waligórska‐Stachura Poland
Naoko Iwasa Japan
Jingcheng Liu China
Jung Uee Lee South Korea
Fernando L‐López relative to Sergio Pedraza‐Arévalo Spain Sergio Pedraza‐Arévalo's profile →
Citations per field
00.5×1.5×
Sergio Pedraza‐Arévalo · 1×
Citations per year

Countries citing papers authored by Fernando L‐López

Since Specialization
Citations

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

Fields of papers citing papers by Fernando L‐López

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernando L‐López. 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 Fernando L‐López. The network helps show where Fernando L‐López may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202056
2 202053
3 201743
4 201841
5 201738
6 201932
7 201731
8 201629
9 201721
10 201918
11 202015
12 202213
13 201912
14 201711
15 201911
16 201511
17 20168
18 20218
19 19862
20
Polimorfismo genético en los receptores de la hormona del crecimiento y prolactina en el Siboney de Cuba: Desarrollo de metodologías
20121

About Fernando L‐López

Fernando L‐López is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Epidemiology, Physiology and Cancer Research, having authored 22 papers that have together received 456 indexed citations. Recurring topics across this work include Metabolism, Diabetes, and Cancer (6 papers), Pituitary Gland Disorders and Treatments (5 papers), RNA Research and Splicing (4 papers), Adipose Tissue and Metabolism (4 papers), Cancer, Hypoxia, and Metabolism (4 papers), Growth Hormone and Insulin-like Growth Factors (4 papers), Neuroendocrine Tumor Research Advances (4 papers) and Prostate Cancer Treatment and Research (3 papers). The work is most often cited by research in Cancer Research (132 citations), Endocrine and Autonomic Systems (34 citations), Endocrinology, Diabetes and Metabolism (73 citations), Molecular Biology (276 citations) and Epidemiology (110 citations). Fernando L‐López has collaborated with scholars based in Spain, United States and Italy. Frequent co-authors include Raúl M. Luque, Manuel D. Gahete, Justo P. Castaño, André Sarmento‐Cabral, Sergio Pedraza‐Arévalo, Juan M. Jiménez‐Vacas, Rafael Sánchez‐Sánchez, Aura D. Herrera‐Martínez, María Ángeles Gálvez-Moreno and Alejandro Ibáñez‐Costa. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Endocrinology, Journal of Clinical Medicine, Neuroendocrinology and Cancer Letters.

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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