Daniel Cimbora

3.7k citations
36 papers · 2.2k indexed · 1 hit paper · h-index 21

Impact in

Papers in

Daniel Cimbora

35 papers receiving 2.2k citations

Hit Papers

The Protein Network of HIV Budding 2003 · 689 citations
6892003202620102018200400600

Peers

Daniel Cimbora
Comparison fields: 5 of 103
  • Virology 276
  • Cell Biology 421
  • Molecular Biology 1.4k
  • Immunology 307
  • Pathology and Forensic Medicine 236
Replace Meg Trahey with:
Meg Trahey United States
Jamal Tazi France
Andrew Y. Choo United States
Yegor Vassetzky France
Terry Copeland United States
Cheng-Ming Chiang United States
Su‐Fang Lin Taiwan
Apurva Sarin India
R Ben-Levy Israel
Scott Briggs United States
Daniel Cimbora relative to Meg Trahey United States Meg Trahey's profile →
Citations per field
00.5×4.0×
Meg Trahey · 1×
Citations per year

Countries citing papers authored by Daniel Cimbora

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Cimbora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The Protein Network of HIV Budding
Hit paper breakdown →
2003689
2 2000279
3 1998170
4 1998143
5 2000134
6 200097
7 201890
8 200890
9 201660
10 200250
11 201049
12 199548
13 202141
14 200137
15 201236
16 201226
17 202126
18 202124
19 201124
20 202420

About Daniel Cimbora

Daniel Cimbora is a scholar working on Molecular Biology, Pathology and Forensic Medicine, Immunology, Neurology and Cell Biology, having authored 36 papers that have together received 2.2k indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (11 papers), Peripheral Neuropathies and Disorders (7 papers), Genomics and Chromatin Dynamics (6 papers), DNA and Nucleic Acid Chemistry (5 papers), Epigenetics and DNA Methylation (4 papers), Microtubule and mitosis dynamics (3 papers), Immunotherapy and Immune Responses (3 papers) and Monoclonal and Polyclonal Antibodies Research (3 papers). The work is most often cited by research in Virology (276 citations), Cell Biology (421 citations), Molecular Biology (1.4k citations), Immunology (307 citations) and Pathology and Forensic Medicine (236 citations). Daniel Cimbora has collaborated with scholars based in United States, Germany and Japan. Frequent co-authors include Mark Groudine, Andreas Reik, Dirk Schübeler, David I. K. Martin, Claire Francastel, Elliot Epner, Agnes Telling, Thaylon Davis, Jerry Kaplan and Scott G. Morham. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, Molecular and Cellular Biology, Multiple Sclerosis Journal, Cancer Research and Multiple Sclerosis and Related Disorders.

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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