Daniel L. Galvan

2.6k citations
35 papers · 2.2k · h-index 21

Impact in

Papers in

Daniel L. Galvan

34 papers receiving 2.2k citations

Peers

Daniel L. Galvan
Comparison fields: 5 of 120
  • Nephrology 260
  • Clinical Biochemistry 240
  • Cancer Research 311
  • Molecular Biology 1.4k
  • Physiology 54
Replace Björn Friedrich with:
Björn Friedrich Germany
Sayon Roy United States
Ping H. Wang United States
Joshua J. Wang United States
Hyug Moo Kwon South Korea
Syamantak Majumder India
W S Lee United States
Ying H. Shen China
M. S. Simonson United States
Denis Féliers United States
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Citations per field
00.5×2×3×4×4.9×
Björn Friedrich · 1×
Citations per year

Countries citing papers authored by Daniel L. Galvan

Since Specialization
Citations

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

Fields of papers citing papers by Daniel L. Galvan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017370
2 2016320
3 2008303
4 2016158
5 2009111
6 201997
7 199975
8 201974
9 199873
10 201770
11 199969
12 200963
13 201158
14 200237
15 201733
16 201732
17 202030
18 202126
19 199823
20 202423

About Daniel L. Galvan

Daniel L. Galvan is a scholar working on Clinical Biochemistry, Molecular Biology, Genetics, Oncology and Physiology, having authored 35 papers that have together received 2.2k indexed citations. Recurring topics across this work include Mitochondrial Function and Pathology (9 papers), CRISPR and Genetic Engineering (8 papers), Metabolism and Genetic Disorders (7 papers), Virus-based gene therapy research (6 papers), CAR-T cell therapy research (5 papers), RNA Interference and Gene Delivery (4 papers), Cancer-related molecular mechanisms research (3 papers) and Engineering Education and Curriculum Development (2 papers). The work is most often cited by research in Nephrology (260 citations), Clinical Biochemistry (240 citations), Cancer Research (311 citations), Molecular Biology (1.4k citations) and Physiology (54 citations). Daniel L. Galvan has collaborated with scholars based in United States, Japan and China. Frequent co-authors include Farhad R. Danesh, Benny Hung‐Junn Chang, Shawn S. Badal, Jianyin Long, Yin Wang, Bernard A. Ayanga, Gregory A. Mignery, Paul A. Overbeek, Matthew H. Wilson and Paul T. Schumacker. Their work appears in journals such as Journal of Biological Chemistry, Kidney International, Journal of the American Society of Nephrology, Journal of Clinical Investigation and Molecular Therapy.

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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