Mads Heuckendorff

28 total papers · 610 total citations
22 papers, 526 citations indexed

About

Mads Heuckendorff is a scholar working on Organic Chemistry, Molecular Biology and Plant Science. According to data from OpenAlex, Mads Heuckendorff has authored 22 papers receiving a total of 526 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Organic Chemistry, 17 papers in Molecular Biology and 5 papers in Plant Science. Recurrent topics in Mads Heuckendorff's work include Carbohydrate Chemistry and Synthesis (20 papers), Glycosylation and Glycoproteins Research (13 papers) and Chemical Synthesis and Analysis (6 papers). Mads Heuckendorff is often cited by papers focused on Carbohydrate Chemistry and Synthesis (20 papers), Glycosylation and Glycoproteins Research (13 papers) and Chemical Synthesis and Analysis (6 papers). Mads Heuckendorff collaborates with scholars based in Denmark, United States and United Kingdom. Mads Heuckendorff's co-authors include Mikael Bols, Christian Pedersen, Henrik H. Jensen, Tobias Gylling Frihed, Jesper Bendix, Papapida Pornsuriyasak, Anders Ø. Madsen, Alexei V. Demchenko, A. Pujol and Thomas Helmer Pedersen and has published in prestigious journals such as Angewandte Chemie International Edition, Chemical Communications and Journal of Cleaner Production.

In The Last Decade

Mads Heuckendorff

21 papers receiving 524 citations

Author Peers

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

Author Last Decade Papers Cites
Mads Heuckendorff 493 426 76 29 22 22 526
Torbjoern Frejd 444 0.9× 333 0.8× 55 0.7× 35 1.2× 18 0.8× 12 509
Yiqun Geng 424 0.9× 385 0.9× 170 2.2× 37 1.3× 19 0.9× 13 576
Karen Plé 319 0.6× 302 0.7× 58 0.8× 32 1.1× 27 1.2× 26 618
Narayana Murthy Sabbavarapu 406 0.8× 313 0.7× 40 0.5× 26 0.9× 16 0.7× 16 518
Robert Rodebaugh 436 0.9× 347 0.8× 71 0.9× 32 1.1× 15 0.7× 11 479
Gaoyan Lian 486 1.0× 345 0.8× 80 1.1× 43 1.5× 48 2.2× 21 612
Penghua Li 455 0.9× 248 0.6× 54 0.7× 18 0.6× 33 1.5× 35 578
Jin‐Xi Liao 413 0.8× 327 0.8× 37 0.5× 32 1.1× 45 2.0× 35 526
Tobias Gylling Frihed 496 1.0× 346 0.8× 62 0.8× 34 1.2× 35 1.6× 13 551
P. A. M. VAN DER KLEIN 503 1.0× 410 1.0× 64 0.8× 40 1.4× 36 1.6× 22 580

Countries citing papers authored by Mads Heuckendorff

Since Specialization
Citations

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

Fields of papers citing papers by Mads Heuckendorff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mads Heuckendorff

This figure shows the co-authorship network connecting the top 25 collaborators of Mads Heuckendorff. A scholar is included among the top collaborators of Mads Heuckendorff 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 Mads Heuckendorff. Mads Heuckendorff 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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