Kim de Mora

12 total papers · 697 total citations
8 papers, 461 citations indexed

About

Kim de Mora is a scholar working on Molecular Biology, Genetics and Biophysics. According to data from OpenAlex, Kim de Mora has authored 8 papers receiving a total of 461 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Genetics and 2 papers in Biophysics. Recurrent topics in Kim de Mora's work include Gene Regulatory Network Analysis (4 papers), Cell Image Analysis Techniques (2 papers) and Bacterial Genetics and Biotechnology (2 papers). Kim de Mora is often cited by papers focused on Gene Regulatory Network Analysis (4 papers), Cell Image Analysis Techniques (2 papers) and Bacterial Genetics and Biotechnology (2 papers). Kim de Mora collaborates with scholars based in United States, United Kingdom and Japan. Kim de Mora's co-authors include Jason Kelly, Caroline M. Ajo‐Franklin, Michael J. Czar, Dileep D. Monie, Adam J. Rubin, John Cumbers, Drew Endy, Joseph H. Davis, Markus Gershater and Traci Haddock-Angelli and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and BMC Systems Biology.

In The Last Decade

Kim de Mora

8 papers receiving 451 citations

Author Peers

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

Author Last Decade Papers Cites
Kim de Mora 403 140 41 38 32 8 461
Jason Kelly 378 0.9× 121 0.9× 34 0.8× 43 1.1× 27 0.8× 9 435
Ying-Ja Chen 374 0.9× 187 1.3× 6 0.1× 53 1.4× 43 1.3× 7 454
Szilvia Kiriakov 335 0.8× 60 0.4× 14 0.3× 63 1.7× 19 0.6× 9 410
Jacob R. Rubens 419 1.0× 62 0.4× 18 0.4× 104 2.7× 20 0.6× 5 491
Fahim Farzadfard 480 1.2× 101 0.7× 12 0.3× 47 1.2× 76 2.4× 10 527
Gemma Perez-Samper 291 0.7× 84 0.6× 14 0.3× 46 1.2× 20 0.6× 7 410
Jolanta Zaim 350 0.9× 155 1.1× 12 0.3× 10 0.3× 31 1.0× 8 450
Joe C. Liang 516 1.3× 64 0.5× 11 0.3× 76 2.0× 22 0.7× 7 537
Evan J. Olson 440 1.1× 72 0.5× 48 1.2× 77 2.0× 29 0.9× 10 538
Jed Dean 347 0.9× 116 0.8× 5 0.1× 48 1.3× 28 0.9× 8 411

Countries citing papers authored by Kim de Mora

Since Specialization
Citations

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

Fields of papers citing papers by Kim de Mora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kim de Mora

This figure shows the co-authorship network connecting the top 25 collaborators of Kim de Mora. A scholar is included among the top collaborators of Kim de Mora 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 de Mora. Kim de Mora 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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