Monica Z. Wang

1.2k total citations
10 papers, 942 citations indexed

About

Monica Z. Wang is a scholar working on Molecular Biology, Neurology and Virology. According to data from OpenAlex, Monica Z. Wang has authored 10 papers receiving a total of 942 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Neurology and 2 papers in Virology. Recurrent topics in Monica Z. Wang's work include Amyotrophic Lateral Sclerosis Research (4 papers), HIV Research and Treatment (2 papers) and biodegradable polymer synthesis and properties (2 papers). Monica Z. Wang is often cited by papers focused on Amyotrophic Lateral Sclerosis Research (4 papers), HIV Research and Treatment (2 papers) and biodegradable polymer synthesis and properties (2 papers). Monica Z. Wang collaborates with scholars based in United States, Switzerland and Germany. Monica Z. Wang's co-authors include John Lincecum, Linda C. Burkly, Beth Browning, Timothy S. Zheng, Jennifer S. Michaelson, D. Montgomery Bissell, Bruce Wang, Aniela Jakubowski, Christine Ambrose and Michael Parr and has published in prestigious journals such as Journal of Clinical Investigation, Nature Medicine and Nature Genetics.

In The Last Decade

Monica Z. Wang

10 papers receiving 924 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Monica Z. Wang United States 9 460 230 171 168 159 10 942
Nicolas Gadot France 20 520 1.1× 108 0.5× 123 0.7× 30 0.2× 44 0.3× 46 990
Maria Kontogiannea Canada 13 853 1.9× 163 0.7× 140 0.8× 33 0.2× 243 1.5× 17 1.3k
Michael Strehle Germany 7 544 1.2× 48 0.2× 44 0.3× 344 2.0× 55 0.3× 7 987
I‐Chu Tseng United States 13 256 0.6× 138 0.6× 92 0.5× 81 0.5× 32 0.2× 15 630
Hartmut Berns United States 8 388 0.8× 116 0.5× 61 0.4× 36 0.2× 24 0.2× 8 658
Alexandra Demory Germany 10 323 0.7× 61 0.3× 189 1.1× 158 0.9× 11 0.1× 15 830
William E. Dowdle United States 12 1.1k 2.4× 81 0.4× 82 0.5× 15 0.1× 93 0.6× 17 1.5k
Gary Meyer United States 9 403 0.9× 84 0.4× 56 0.3× 22 0.1× 44 0.3× 19 917
Carsten F. Rundsten Denmark 6 398 0.9× 187 0.8× 90 0.5× 16 0.1× 48 0.3× 6 800
Osman N. Özeş United States 13 649 1.4× 364 1.6× 334 2.0× 58 0.3× 9 0.1× 31 1.1k

Countries citing papers authored by Monica Z. Wang

Since Specialization
Citations

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

Fields of papers citing papers by Monica Z. Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Monica Z. Wang

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

All Works

10 of 10 papers shown
1.
Wang, Monica Z., et al.. (2019). Primary Neurons and Differentiated NSC-34 Cells Are More Susceptible to Arginine-Rich ALS Dipeptide Repeat Protein-Associated Toxicity than Non-Differentiated NSC-34 and CHO Cells. International Journal of Molecular Sciences. 20(24). 6238–6238. 11 indexed citations
2.
Hatzipetros, Theo, Joshua D. Kidd, Beth Levine, et al.. (2019). SOD1-positive aggregate accumulation in the CNS predicts slower disease progression and increased longevity in a mutant SOD1 mouse model of ALS. Scientific Reports. 9(1). 6724–6724. 50 indexed citations
3.
Vieira, Fernando G., Joshua D. Kidd, Kenneth Thompson, et al.. (2015). Guanabenz Treatment Accelerates Disease in a Mutant SOD1 Mouse Model of ALS. PLoS ONE. 10(8). e0135570–e0135570. 64 indexed citations
4.
Lincecum, John, Fernando G. Vieira, Monica Z. Wang, et al.. (2010). From transcriptome analysis to therapeutic anti-CD40L treatment in the SOD1 model of amyotrophic lateral sclerosis. Nature Genetics. 42(5). 392–399. 96 indexed citations
5.
Michaelson, Jennifer S., Beth Browning, Timothy S. Zheng, et al.. (2005). Tweak induces mammary epithelial branching morphogenesis. Oncogene. 24(16). 2613–2624. 73 indexed citations
6.
Jakubowski, Aniela, Christine Ambrose, Michael Parr, et al.. (2005). TWEAK induces liver progenitor cell proliferation. Journal of Clinical Investigation. 115(9). 2330–2340. 329 indexed citations
7.
Zhang, Wen, Linda C. Burkly, Kyungmin Hahm, et al.. (2004). Tumor Necrosis Factor-Like Weak Inducer of Apoptosis-Induced Neurodegeneration. Journal of Neuroscience. 24(38). 8237–8244. 120 indexed citations
8.
Granowitz, Eric V., Jonathan B. Angel, Monica Z. Wang, et al.. (1996). Soluble Tumor Necrosis Factor Receptors Inhibit Phorbol Myristate Acetate and Cytokine-Induced HIV-1 Expression Chronically Infected U1 Cells. PubMed. 11(5). 430–437. 6 indexed citations
9.
Wang, Monica Z., David Bumcrot, Valeria Marigo, et al.. (1995). Induction of dopaminergic neuron phenotype in the midbrain by Sonic hedgehog protein. Nature Medicine. 1(11). 1184–1188. 141 indexed citations
10.

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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