Kim D. Pruitt

167 total papers · 55.9k total citations
63 papers, 17.1k citations indexed

About

Kim D. Pruitt is a scholar working on Molecular Biology, Ecology and Genetics. According to data from OpenAlex, Kim D. Pruitt has authored 63 papers receiving a total of 17.1k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Molecular Biology, 10 papers in Ecology and 7 papers in Genetics. Recurrent topics in Kim D. Pruitt's work include Genomics and Phylogenetic Studies (35 papers), RNA and protein synthesis mechanisms (18 papers) and Bacteriophages and microbial interactions (9 papers). Kim D. Pruitt is often cited by papers focused on Genomics and Phylogenetic Studies (35 papers), RNA and protein synthesis mechanisms (18 papers) and Bacteriophages and microbial interactions (9 papers). Kim D. Pruitt collaborates with scholars based in United States, United Kingdom and Switzerland. Kim D. Pruitt's co-authors include Tatiana Tatusova, James Ostell, Donna Maglott, Michael DiCuccio, Alexandre Lomsadze, Eric P. Nawrocki, Mark Borodovsky, Leonid Zaslavsky, Vyacheslav Chetvernin and Azat Badretdin and has published in prestigious journals such as Nucleic Acids Research, Nature Genetics and PLoS ONE.

In The Last Decade

Kim D. Pruitt

61 papers receiving 16.9k citations

Hit Papers

NCBI prokaryotic genome a... 2001 2026 2009 2017 2016 2006 2004 2010 2011 1000 2.0k 3.0k 4.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation benchmark for papers published in the same subfield and year, or reaches the top citation threshold in at least one of its specific research topics.

  1. NCBI prokaryotic genome annotation pipeline
    2016 4.5k citations Tatiana Tatusova, Michael DiCuccio et al. Nucleic Acids Research profile →
  2. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins
    2006 3.4k citations Kim D. Pruitt, Tatiana Tatusova et al. Nucleic Acids Research profile →
  3. NCBI Reference Sequence (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins
    2004 1.3k citations Kim D. Pruitt Nucleic Acids Research profile →
  4. Entrez Gene: gene-centered information at NCBI
    2010 1.2k citations Donna Maglott, James Ostell et al. Nucleic Acids Research profile →
  5. NCBI Reference Sequences (RefSeq): current status, new features and genome annotation policy
    2011 874 citations Kim D. Pruitt, Tatiana Tatusova et al. Nucleic Acids Research profile →
  6. RefSeq and LocusLink: NCBI gene-centered resources
    2001 695 citations Kim D. Pruitt Nucleic Acids Research profile →
  7. NCBI Reference Sequences: current status, policy and new initiatives
    2008 610 citations Kim D. Pruitt, Tatiana Tatusova et al. Nucleic Acids Research profile →
  8. GenBank
    2017 505 citations D. A. Benson, Mark Cavanaugh et al. Nucleic Acids Research profile →
  9. Gene: a gene-centered information resource at NCBI
    2014 481 citations Garth Brown, Kenneth Katz et al. Nucleic Acids Research profile →
  10. GenBank
    2018 334 citations Eric W Sayers, Mark Cavanaugh et al. Nucleic Acids Research profile →
  11. Rapid and sensitive detection of genome contamination at scale with FCS-GX
    2024 93 citations Eric S. Tvedte, Deacon Sweeney et al. Genome biology profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Kim D. Pruitt 12.4k 3.1k 2.5k 2.0k 1.0k 63 17.1k
Tatiana Tatusova 12.0k 1.0× 3.3k 1.1× 2.7k 1.1× 2.0k 1.0× 829 0.8× 59 17.6k
Yanqing Zhou 7.8k 0.6× 2.6k 0.9× 3.9k 1.5× 2.2k 1.1× 1.1k 1.0× 84 15.8k
Jia Gu 7.5k 0.6× 2.6k 0.9× 3.7k 1.5× 2.2k 1.1× 1.1k 1.0× 42 15.4k
Todd M. Lowe 15.2k 1.2× 5.5k 1.8× 3.9k 1.6× 2.5k 1.2× 1.1k 1.1× 62 20.1k
James Ostell 11.1k 0.9× 3.9k 1.3× 3.0k 1.2× 2.1k 1.0× 530 0.5× 36 19.7k
Shifu Chen 8.0k 0.6× 2.7k 0.9× 3.9k 1.5× 2.3k 1.1× 1.3k 1.2× 143 17.1k
Marco Punta 10.5k 0.8× 2.1k 0.7× 4.0k 1.6× 1.8k 0.9× 721 0.7× 59 15.2k
Sofia K. Forslund 16.8k 1.4× 3.5k 1.1× 4.0k 1.6× 2.7k 1.3× 1.7k 1.6× 97 25.3k
James Taylor 10.4k 0.8× 2.3k 0.7× 2.1k 0.8× 2.1k 1.0× 1.1k 1.1× 91 16.2k
Andreas Heger 10.7k 0.9× 1.7k 0.6× 3.3k 1.3× 2.2k 1.1× 1.3k 1.2× 55 15.9k

Countries citing papers authored by Kim D. Pruitt

Since Specialization
Citations

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

Fields of papers citing papers by Kim D. Pruitt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kim D. Pruitt. 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 Kim D. Pruitt. The network helps show where Kim D. Pruitt may publish in the future.

Co-authorship network of co-authors of Kim D. Pruitt

This figure shows the co-authorship network connecting the top 25 collaborators of Kim D. Pruitt. A scholar is included among the top collaborators of Kim D. Pruitt 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 Kim D. Pruitt. Kim D. Pruitt is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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