T. Neil Dear

53 total papers · 4.3k total citations
41 papers, 1.9k citations indexed

About

T. Neil Dear is a scholar working on Molecular Biology, Cell Biology and Genetics. According to data from OpenAlex, T. Neil Dear has authored 41 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 12 papers in Cell Biology and 8 papers in Genetics. Recurrent topics in T. Neil Dear's work include Calpain Protease Function and Regulation (6 papers), Genomics and Chromatin Dynamics (4 papers) and CRISPR and Genetic Engineering (4 papers). T. Neil Dear is often cited by papers focused on Calpain Protease Function and Regulation (6 papers), Genomics and Chromatin Dynamics (4 papers) and CRISPR and Genetic Engineering (4 papers). T. Neil Dear collaborates with scholars based in United Kingdom, Germany and Australia. T. Neil Dear's co-authors include Thomas Boehm, Terence H. Rabbitts, Ivana Barbaric, Gaynor Miller, N. Meier, Isidro Sánchez‐García, Andrea Brendolan, Richard Kefford, Licia Selleri and Rita Carsetti and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The EMBO Journal.

In The Last Decade

T. Neil Dear

41 papers receiving 1.9k citations

Author Peers

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

Author Last Decade Papers Cites
T. Neil Dear 1.1k 357 341 243 230 41 1.9k
Jean‐Claude Lissitzky 828 0.7× 332 0.9× 378 1.1× 210 0.9× 264 1.1× 53 2.1k
Edith Hintermann 875 0.8× 281 0.8× 299 0.9× 342 1.4× 226 1.0× 61 2.7k
David M. Alvarado 987 0.9× 261 0.7× 420 1.2× 340 1.4× 194 0.8× 55 2.4k
Renata Polakowska 1.3k 1.2× 448 1.3× 190 0.6× 291 1.2× 363 1.6× 51 2.4k
Vincent Ollendorff 1.5k 1.3× 375 1.1× 340 1.0× 458 1.9× 252 1.1× 44 2.4k
Caroline Andrews 1.1k 1.0× 336 0.9× 434 1.3× 460 1.9× 226 1.0× 60 2.8k
Masando Hayashi 991 0.9× 437 1.2× 422 1.2× 222 0.9× 230 1.0× 55 2.6k
Petra Kioschis 1.8k 1.6× 168 0.5× 446 1.3× 269 1.1× 253 1.1× 41 2.5k
James D. Eudy 1.2k 1.1× 187 0.5× 300 0.9× 228 0.9× 179 0.8× 46 2.1k
Francis James Grant 1.5k 1.4× 282 0.8× 374 1.1× 353 1.5× 246 1.1× 33 3.1k

Countries citing papers authored by T. Neil Dear

Since Specialization
Citations

This map shows the geographic impact of T. Neil Dear'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 T. Neil Dear with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Neil Dear more than expected).

Fields of papers citing papers by T. Neil Dear

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T. Neil Dear. 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 T. Neil Dear. The network helps show where T. Neil Dear may publish in the future.

Co-authorship network of co-authors of T. Neil Dear

This figure shows the co-authorship network connecting the top 25 collaborators of T. Neil Dear. A scholar is included among the top collaborators of T. Neil Dear 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 T. Neil Dear. T. Neil Dear 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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