Kanny K. Wan

520 total citations
11 papers, 393 citations indexed

About

Kanny K. Wan is a scholar working on Organic Chemistry, Molecular Biology and Physiology. According to data from OpenAlex, Kanny K. Wan has authored 11 papers receiving a total of 393 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Organic Chemistry, 5 papers in Molecular Biology and 3 papers in Physiology. Recurrent topics in Kanny K. Wan's work include Adenosine and Purinergic Signaling (3 papers), Chemical Synthesis and Analysis (3 papers) and Asymmetric Synthesis and Catalysis (2 papers). Kanny K. Wan is often cited by papers focused on Adenosine and Purinergic Signaling (3 papers), Chemical Synthesis and Analysis (3 papers) and Asymmetric Synthesis and Catalysis (2 papers). Kanny K. Wan collaborates with scholars based in United States. Kanny K. Wan's co-authors include Ryan A. Shenvi, Kotaro Iwasaki, Steven W. M. Crossley, Alberto Oppedisano, David A. Vosburg, Jeffrey C. Umotoy, Dennis W. Wolan, Samarjit Patnaik, Alexander G. Godfrey and Dipanwita Basu and has published in prestigious journals such as Journal of the American Chemical Society, Angewandte Chemie International Edition and Science Translational Medicine.

In The Last Decade

Kanny K. Wan

10 papers receiving 389 citations

Peers

Kanny K. Wan

OC

MB

PHARM

IC

BIOTE

Alberto Oppedisano Italy

Yoshitaka Numajiri United States

Artur K. Mailyan United States

Danai S. Gkotsi United Kingdom

Xiao Zheng China

Paul S. Riehl United States

Elena M. Sánchez Spain

Timothy R. Hightower United States

Michael L. Conner United States

Shogo Kamo Japan

Alberto Oppedisano Italy

Kanny K. Wan

381 ×1.3

OC

78 ×1.0

MB

48 ×0.7

PHARM

90 ×1.5

IC

45 ×0.9

BIOTE

Citations per year, relative to Kanny K. Wan Kanny K. Wan (= 1×) peers Alberto Oppedisano

Countries citing papers authored by Kanny K. Wan

Since Specialization

Citations

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

Fields of papers citing papers by Kanny K. Wan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kanny K. Wan. 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 Kanny K. Wan. The network helps show where Kanny K. Wan may publish in the future.

Co-authorship network of co-authors of Kanny K. Wan

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

All Works

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11 of 11 papers shown

1.

Zahoránszky-Köhalmi, Gergely, Kanny K. Wan, & Alexander G. Godfrey. (2024). Hilbert-curve assisted structure embedding method. Journal of Cheminformatics. 16(1). 87–87. 2 indexed citations

2.

Comba, Işın Y., Eli Silvert, Michiel J.M. Niesen, et al.. (2024). A deep learning approach predicting the activity of COVID-19 therapeutics and vaccines against emerging variants. npj Systems Biology and Applications. 10(1). 138–138.

3.

Kurowski, Agata, et al.. (2022). Selective Inhibitors of Autophagy Reveal New Link between the Cell Cycle and Autophagy and Lead to Discovery of Novel Synergistic Drug Combinations. ACS Chemical Biology. 17(12). 3290–3297. 3 indexed citations

4.

Caffall, Zachary F., Bradley J. Wilkes, Ricardo Hernández, et al.. (2021). The HIV protease inhibitor, ritonavir, corrects diverse brain phenotypes across development in mouse model of DYT-TOR1A dystonia. Science Translational Medicine. 13(607). 17 indexed citations

5.

Patnaik, Samarjit, Dipanwita Basu, Noel Southall, et al.. (2019). Identification, design and synthesis of novel pyrazolopyridine influenza virus nonstructural protein 1 antagonists. Bioorganic & Medicinal Chemistry Letters. 29(9). 1113–1119. 13 indexed citations

6.

Shenvi, Ryan A. & Kanny K. Wan. (2016). Conjuring a Supernatural Product – DelMarine. Synlett. 27(8). 1145–1164. 17 indexed citations

7.

Wan, Kanny K., Kotaro Iwasaki, Jeffrey C. Umotoy, Dennis W. Wolan, & Ryan A. Shenvi. (2015). Nitrosopurines En Route to Potently Cytotoxic Asmarines. Angewandte Chemie International Edition. 54(8). 2410–2415. 18 indexed citations

8.

Wan, Kanny K., Kotaro Iwasaki, Jeffrey C. Umotoy, Dennis W. Wolan, & Ryan A. Shenvi. (2015). Nitrosopurines En Route to Potently Cytotoxic Asmarines. Angewandte Chemie. 127(8). 2440–2445. 4 indexed citations

9.

Iwasaki, Kotaro, Kanny K. Wan, Alberto Oppedisano, Steven W. M. Crossley, & Ryan A. Shenvi. (2014). Simple, Chemoselective Hydrogenation with Thermodynamic Stereocontrol. Journal of the American Chemical Society. 136(4). 1300–1303. 302 indexed citations

10.

Vosburg, David A., et al.. (2013). Synthesis of cis- and trans-Davanoids: Artemone, Hydroxydavanone, Isodavanone, and Nordavanone. Synthesis. 45(11). 1541–1545. 9 indexed citations

11.

Wan, Kanny K., et al.. (2010). Two-step, stereoselective synthesis of linalyl oxides by asymmetric allylic O-alkylation. Tetrahedron Asymmetry. 21(19). 2425–2428. 8 indexed citations

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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