Tim Kievits

1.9k citations
22 papers · 1.5k · h-index 14

Impact in

  • Virology top 2%
    • HIV Research and Treatment
    • HIV/AIDS drug development and treatment
    • HIV/AIDS Research and Interventions

Papers in

    • Advanced biosensing and bioanalysis techniques 6
    • CRISPR and Genetic Engineering 4
    • Bacteriophages and microbial interactions 7

Tim Kievits

21 papers receiving 1.4k citations

Peers

Tim Kievits
Comparison fields: 5 of 82
  • Virology 382
  • Infectious Diseases 389
  • Genetics 321
  • Cancer Research 134
  • Molecular Biology 615
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Yasuko Tsunetsugu‐Yokota Japan
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Masaru Yokoyama Japan
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Richard Rudersdorf United States
C. de Taisne France
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Citations per field
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Citations per year

Countries citing papers authored by Tim Kievits

Since Specialization
Citations

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

Fields of papers citing papers by Tim Kievits

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1991353
2
Detection of chromosome aneuploidy in interphase nuclei from human primary breast tumors using chromosome-specific repetitive DNA probes.
1988214
3 1994193
4 1988114
5 1993114
6 1988101
7
Frequent somatic imbalance of marker alleles for chromosome 1 in human primary breast carcinoma.
199194
8 199366
9 199554
10 199053
11 199639
12 200139
13 199536
14 198915
15 199513
16
Activation of the mas oncogene involves coupling to human alphoid sequences.
199313
17 200810
18 19955
19 20083
20 20242

About Tim Kievits

Tim Kievits is a scholar working on Molecular Biology, Ecology, Virology, Genetics and Infectious Diseases, having authored 22 papers that have together received 1.5k indexed citations. Recurring topics across this work include Bacteriophages and microbial interactions (7 papers), HIV Research and Treatment (6 papers), Advanced biosensing and bioanalysis techniques (6 papers), Chromosomal and Genetic Variations (4 papers), CRISPR and Genetic Engineering (4 papers), Cancer-related Molecular Pathways (3 papers), Genomic variations and chromosomal abnormalities (3 papers) and Biosensors and Analytical Detection (2 papers). The work is most often cited by research in Virology (382 citations), Infectious Diseases (389 citations), Genetics (321 citations), Cancer Research (134 citations) and Molecular Biology (615 citations). Tim Kievits has collaborated with scholars based in Netherlands, United States and Canada. Frequent co-authors include Bob van Gemen, Peter Lens, Dianne van Strijp, P. Pearson, Peter Devilee, Roy Sooknanan, R Schukkink, Suzanne Jurriaans, Henriëtte Adriaanse and Rinie van Beuningen. Their work appears in journals such as Genomics, Clinical Chemistry, Biology Methods and Protocols, AIDS and Genome 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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