David Příhoda

752 citations
7 papers · 418 · h-index 6

Impact in

Papers in

    • Genomics and Phylogenetic Studies 2
    • Viral Infectious Diseases and Gene Expression in Insects 2
    • RNA and protein synthesis mechanisms 2
    • Protein purification and stability 1
    • Microbial Natural Products and Biosynthesis 2

David Příhoda

7 papers receiving 405 citations

Peers

David Příhoda
Comparison fields: 5 of 68
  • Pharmacology 138
  • Biotechnology 51
  • Radiology, Nuclear Medicine and Imaging 113
  • Molecular Biology 284
  • Computational Theory and Mathematics 40
Replace Frank V. Ritacco with:
Frank V. Ritacco United States
Kazuharu Hanada Japan
Mayuko Takeda‐Shitaka Japan
Yilong Lian Singapore
David L. Niquille Switzerland
Money Gupta India
Prasun Dutta India
Fu-Lien Hsieh Taiwan
Crystel Barbisan France
Deborah A. Leonard United States
David Příhoda relative to Frank V. Ritacco United States Frank V. Ritacco's profile →
Citations per field
00.5×10×20×27×
Frank V. Ritacco · 1×
Citations per year

Countries citing papers authored by David Příhoda

Since Specialization
Citations

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

Fields of papers citing papers by David Příhoda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

7 of 7 papers shown
#Work
1 2019219
2 2022118
3 202036
4 202320
5 202312
6 202411
7 20232

About David Příhoda

David Příhoda is a scholar working on Molecular Biology, Pharmacology, Radiology, Nuclear Medicine and Imaging, Ecology and Artificial Intelligence, having authored 7 papers that have together received 418 indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (2 papers), Viral Infectious Diseases and Gene Expression in Insects (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Microbial Natural Products and Biosynthesis (2 papers), RNA and protein synthesis mechanisms (2 papers), Speech Recognition and Synthesis (1 paper), Protein purification and stability (1 paper) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Pharmacology (138 citations), Biotechnology (51 citations), Radiology, Nuclear Medicine and Imaging (113 citations), Molecular Biology (284 citations) and Computational Theory and Mathematics (40 citations). David Příhoda has collaborated with scholars based in Czechia, United States and China. Frequent co-authors include Danny A. Bitton, Ondřej Klempíř, Andrew B. Waight, Laurence Fayadat‐Dilman, Christopher H. Woelk, Daria J. Hazuda, Geoffrey D. Hannigan, Daniel Svozil, Veronica Juan and Jad Maamary. Their work appears in journals such as mAbs, Nucleic Acids Research, NAR Genomics and Bioinformatics, Natural Product Reports and Measurement Science Review.

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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