Kevin D. Wells

149 total papers · 8.4k total citations
101 papers, 4.9k citations indexed

About

Kevin D. Wells is a scholar working on Molecular Biology, Genetics and Surgery. According to data from OpenAlex, Kevin D. Wells has authored 101 papers receiving a total of 4.9k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Molecular Biology, 60 papers in Genetics and 18 papers in Surgery. Recurrent topics in Kevin D. Wells's work include Animal Genetics and Reproduction (42 papers), CRISPR and Genetic Engineering (35 papers) and Virus-based gene therapy research (18 papers). Kevin D. Wells is often cited by papers focused on Animal Genetics and Reproduction (42 papers), CRISPR and Genetic Engineering (35 papers) and Virus-based gene therapy research (18 papers). Kevin D. Wells collaborates with scholars based in United States, China and Brazil. Kevin D. Wells's co-authors include Robert M. Petters, Randall S. Prather, R.J. Wall, Melissa Samuel, Neil C. Talbot, Kristin M. Whitworth, Suyapa Ball, Todd Vaught, David Ayares and Eric M. Walters and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Nature Biotechnology.

In The Last Decade

Kevin D. Wells

99 papers receiving 4.7k citations

Hit Papers

Culture of pig embryos. 1993 2026 2004 2015 1993 2002 250 500 750

Author Peers

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

Author Last Decade Papers Cites
Kevin D. Wells 2.8k 2.3k 1.2k 1.0k 481 101 4.9k
Clifton N. Murphy 3.2k 1.2× 3.0k 1.3× 2.0k 1.7× 1.1k 1.1× 498 1.0× 82 5.4k
Melissa Samuel 3.1k 1.1× 2.7k 1.2× 1.3k 1.1× 1.1k 1.1× 167 0.3× 85 4.6k
R.J. Wall 3.7k 1.3× 3.4k 1.5× 963 0.8× 494 0.5× 512 1.1× 110 5.8k
Mette Schmidt 1.5k 0.6× 1.3k 0.6× 1.7k 1.4× 529 0.5× 631 1.3× 126 4.3k
Maria Laura Bacci 1.5k 0.5× 1.0k 0.5× 725 0.6× 409 0.4× 541 1.1× 135 3.2k
Flávio Vieira Meirelles 2.3k 0.8× 1.4k 0.6× 2.0k 1.7× 338 0.3× 853 1.8× 235 4.8k
V. G. Pursel 2.5k 0.9× 2.7k 1.2× 2.3k 1.9× 514 0.5× 2.1k 4.4× 114 5.6k
Masaki Yanagishita 3.3k 1.2× 739 0.3× 852 0.7× 405 0.4× 514 1.1× 130 6.0k
Luc Peelman 2.1k 0.8× 1.2k 0.5× 950 0.8× 208 0.2× 440 0.9× 229 4.6k
Yutaka Toyoda 2.9k 1.1× 1.8k 0.8× 3.1k 2.6× 389 0.4× 2.4k 5.0× 161 6.9k

Countries citing papers authored by Kevin D. Wells

Since Specialization
Citations

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

Fields of papers citing papers by Kevin D. Wells

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin D. Wells

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin D. Wells. A scholar is included among the top collaborators of Kevin D. Wells 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 Kevin D. Wells. Kevin D. Wells 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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