Daniel Rivas

1.6k citations
26 papers · 1.3k · h-index 17

Impact in

Papers in

    • Bone Metabolism and Diseases 5
    • RNA Research and Splicing 4
    • Nuclear Structure and Function 4
    • Bone health and treatments 5

Daniel Rivas

25 papers receiving 1.3k citations

Peers

Daniel Rivas
Comparison fields: 5 of 93
  • Orthopedics and Sports Medicine 320
  • Genetics 142
  • Oncology 247
  • Geriatrics and Gerontology 28
  • Molecular Biology 609
Replace Florence Figeac with:
Florence Figeac France
Ulrike I. Mödder United States
Cristiana Roggia Germany
Claudius E. Robinson United States
Toshio Fumoto Japan
Yuiko Sato Japan
Giulia Maurizi Italy
Antonia Graja Germany
Tami Kobayashi Japan
Igor Gubrij United States
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Citations per field
00.5×3.1×
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Citations per year

Countries citing papers authored by Daniel Rivas

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Rivas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009150
2 2011141
3 2007137
4 2008100
5 200897
6 200997
7 201270
8 201566
9 200958
10 200951
11 200851
12 200647
13 200734
14 202330
15 200924
16 201323
17 202418
18 202416
19 201115
20 201712

About Daniel Rivas

Daniel Rivas is a scholar working on Molecular Biology, Oncology, Orthopedics and Sports Medicine, Physiology and Cardiology and Cardiovascular Medicine, having authored 26 papers that have together received 1.3k indexed citations. Recurring topics across this work include Bone Metabolism and Diseases (5 papers), Bone health and treatments (5 papers), RNA Research and Splicing (4 papers), Nuclear Structure and Function (4 papers), Bone health and osteoporosis research (3 papers), Bone and Joint Diseases (3 papers), Cellular Mechanics and Interactions (2 papers) and Nutrition and Health in Aging (2 papers). The work is most often cited by research in Orthopedics and Sports Medicine (320 citations), Genetics (142 citations), Oncology (247 citations), Geriatrics and Gerontology (28 citations) and Molecular Biology (609 citations). Daniel Rivas has collaborated with scholars based in Canada, Australia and Spain. Frequent co-authors include Gustavo Duque, Jeffrey M. Gimble, Xiying Wu, Rahima Akter, Dao Chao Huang, Michael Macoritto, Richard Kremer, Xian Yang, Wei Li and Stéphanie Lehoux. Their work appears in journals such as Journal of Bone and Mineral Research, Experimental Gerontology, Mechanisms of Ageing and Development, Pacing and Clinical Electrophysiology and Circulation 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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