Daniel V. LaBarbera

2.5k citations
54 papers · 1.9k indexed · 1 hit paper · h-index 24
Topics
Aldose Reductase and Taurine (8 papers)Cancer Cells and Metastasis (8 papers)Cancer therapeutics and mechanisms (7 papers)

In The Last Decade

Daniel V. LaBarbera

53 papers receiving 1.9k citations

Hit Papers

Genetic Analysis of 779 Advanced Differentiated and Anapl...20182026202020232018100200300

Peers

Daniel V. LaBarbera
Comparison fields: 5 of 110
  • Molecular Biology 726
  • Oncology 521
  • Endocrinology, Diabetes and Metabolism 475
  • Biomedical Engineering 293
  • Cell Biology 201
Replace Brian H. Shilton with:
Brian H. Shilton Canada
Chih‐Pin Chuu Taiwan
Christopher R. Ireson United Kingdom
J. Vázquez France
Yanna Cheng China
William H. Tolleson United States
Janusz Skierski Poland
Dexin Kong China
Lorraine M. Deck United States
Tatsushi Yoshida Japan
Daniel V. LaBarbera relative to Brian H. Shilton Canada Brian H. Shilton's profile →
Citations per field
00.5×10×12.7×
Brian H. Shilton · 1×
Citations per year

Countries citing papers authored by Daniel V. LaBarbera

Since Specialization
Citations

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

Fields of papers citing papers by Daniel V. LaBarbera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel V. LaBarbera

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel V. LaBarbera. A scholar is included among the top collaborators of Daniel V. LaBarbera based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel V. LaBarbera. Daniel V. LaBarbera is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 3
2 1
3 2
4 11
5 7
6 23
7 16
8 12
9
Genetic Analysis of 779 Advanced Differentiated and Anaplastic Thyroid Cancersbreakdown →
374
10 42
11 2
12 29
13 24
14 1
15 200
16 45
17 89
18
Halogenated cyclic peptides isolated from the sponge Corticium sp.
1
19 38
20 35

About Daniel V. LaBarbera

Daniel V. LaBarbera is a scholar working on Biotechnology, Toxicology and Biophysics, having authored 54 papers that have together received 1.9k indexed citations. Recurring topics across this work include Aldose Reductase and Taurine (8 papers), Cancer Cells and Metastasis (8 papers) and Cancer therapeutics and mechanisms (7 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (475 citations), Oncology (521 citations) and Toxicology (65 citations). Daniel V. LaBarbera has collaborated with scholars based in United States, Hungary and Brazil. Frequent co-authors include J. Mark Petrash, Byong Hoon Yoo, Brian G. Reid, Qiong Zhou, David G. Holm, Sastry S. Jayanty, Linfeng Li, Diganta Kalita, Jessica Ponder and Kun‐Che Chang. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and PLoS ONE.

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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