Nancy S. Wang

588 total citations
7 papers, 460 citations indexed

About

Nancy S. Wang is a scholar working on Molecular Biology, Infectious Diseases and Computational Theory and Mathematics. According to data from OpenAlex, Nancy S. Wang has authored 7 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 2 papers in Infectious Diseases and 2 papers in Computational Theory and Mathematics. Recurrent topics in Nancy S. Wang's work include Cell death mechanisms and regulation (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Computational Drug Discovery Methods (2 papers). Nancy S. Wang is often cited by papers focused on Cell death mechanisms and regulation (3 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Computational Drug Discovery Methods (2 papers). Nancy S. Wang collaborates with scholars based in United States, Sweden and Ireland. Nancy S. Wang's co-authors include Clark Distelhorst, Edmunds Reineks, Mikko Unkila, Zhengqi Wang, Michael J. Thomenius, Ann‐Charlotte Johansson, Juliane M. Jürgensmeier, Karin Öllinger, Uno Johansson and Karin Roberg and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Medicinal Chemistry and Molecular Therapy.

In The Last Decade

Nancy S. Wang

6 papers receiving 454 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Nancy S. Wang United States	5	290	105	74	66	57	7	460
Yukang Gong China	12	336 1.2×	156 1.5×	68 0.9×	83 1.3×	16 0.3×	12	540
Ursula Bodendorf Switzerland	11	336 1.2×	46 0.4×	56 0.8×	55 0.8×	66 1.2×	17	595
Jianping Liu China	16	491 1.7×	279 2.7×	38 0.5×	165 2.5×	63 1.1×	29	796
Álvaro Lorente‐Macías Spain	6	165 0.6×	48 0.5×	41 0.6×	22 0.3×	45 0.8×	15	345
Mads Nygaard Denmark	8	293 1.0×	150 1.4×	22 0.3×	49 0.7×	10 0.2×	11	425
Shengchen Lin China	13	371 1.3×	62 0.6×	21 0.3×	103 1.6×	36 0.6×	17	678
H Liu China	10	361 1.2×	89 0.8×	18 0.2×	18 0.3×	35 0.6×	21	495
Ben Powell United Kingdom	11	704 2.4×	77 0.7×	47 0.6×	42 0.6×	12 0.2×	20	891
Martin Hénault United States	12	228 0.8×	34 0.3×	38 0.5×	11 0.2×	28 0.5×	15	431
Shahin Ramazi Iran	8	546 1.9×	43 0.4×	17 0.2×	45 0.7×	41 0.7×	8	770

Countries citing papers authored by Nancy S. Wang

Since Specialization

Citations

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

Fields of papers citing papers by Nancy S. Wang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nancy S. Wang. 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 Nancy S. Wang. The network helps show where Nancy S. Wang may publish in the future.

Co-authorship network of co-authors of Nancy S. Wang

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

All Works

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7 of 7 papers shown

Coker, Jesse A., Christopher M. Goins, Sang Hoon Han, et al.. (2024). Discovery and Characterization of Selective, First-in-Class Inhibitors of Citron Kinase. Journal of Medicinal Chemistry. 67(4). 2631–2666. 3 indexed citations

Hooper, Alice, Jonathan D. Macdonald, Sang Hoon Han, et al.. (2023). SARS-CoV-2 3CL-protease inhibitors derived from ML300: investigation of P1 and replacements of the 1,2,3-benzotriazole. Medicinal Chemistry Research. 32(7). 1383–1390.

Han, Sang Hoon, Christopher M. Goins, Woo-Jin Shin, et al.. (2021). Structure-Based Optimization of ML300-Derived, Noncovalent Inhibitors Targeting the Severe Acute Respiratory Syndrome Coronavirus 3CL Protease (SARS-CoV-2 3CL^pro). Journal of Medicinal Chemistry. 65(4). 2880–2904. 87 indexed citations

Reading, James L., Bart Vaes, Caroline Hull, et al.. (2015). Suppression of IL-7-dependent Effector T-cell Expansion by Multipotent Adult Progenitor Cells and PGE2. Molecular Therapy. 23(11). 1783–1793. 35 indexed citations

Kågedal, Katarina, Ann‐Charlotte Johansson, Uno Johansson, et al.. (2005). Lysosomal membrane permeabilization during apoptosis ‐ involvement of Bax?. International Journal of Experimental Pathology. 86(5). 309–321. 106 indexed citations

Thomenius, Michael J., Nancy S. Wang, Edmunds Reineks, Zhengqi Wang, & Clark Distelhorst. (2003). Bcl-2 on the Endoplasmic Reticulum Regulates Bax Activity by Binding to BH3-only Proteins. Journal of Biological Chemistry. 278(8). 6243–6250. 76 indexed citations

Wang, Nancy S., Mikko Unkila, Edmunds Reineks, & Clark Distelhorst. (2001). Transient Expression of Wild-type or Mitochondrially Targeted Bcl-2 Induces Apoptosis, whereas Transient Expression of Endoplasmic Reticulum-targeted Bcl-2 Is Protective against Bax-induced Cell Death. Journal of Biological Chemistry. 276(47). 44117–44128. 153 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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