Mary Wu

6.3k citations
27 papers · 2.8k · 2 hit papers · h-index 18

Impact in

Papers in

Mary Wu

25 papers receiving 2.8k citations

Mary Wu's Hit Papers

TGF-β Superfamily Signaling in Embryonic Development and Homeostasis 2009 · 596 citations
5960+6+12Years since publication2505007501000

Peers

Mary Wu
Comparison fields: 5 of 121
  • Aging 71
  • Cancer Research 443
  • Cell Biology 401
  • Endocrinology 123
  • Molecular Biology 1.6k
Replace Mariola J. Edelmann with:
Mariola J. Edelmann United States
Sei Yoshida Japan
Xiao‐Bo Qiu China
Guillaume Bossis France
Shih-Feng Tsai Taiwan
Xiaoying Zhou China
Jianping Zhang China
Lingqiang Zhang China
Luis del Peso Spain
Michal R. Schweiger Germany
Mary Wu relative to Mariola J. Edelmann United States Mariola J. Edelmann's profile →
Citations per field
00.5×1.5×2.4×
Mariola J. Edelmann · 1×
Citations per year

Countries citing papers authored by Mary Wu

Since Specialization
Citations

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

Fields of papers citing papers by Mary Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mary Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mary Wu Line = papers co-authored together Mary Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1
SREBP Activity Is Regulated by mTORC1 and Contributes to Akt-Dependent Cell Growth
Hit paper breakdown →
20081119
2
TGF-β Superfamily Signaling in Embryonic Development and Homeostasis
Hit paper breakdown →
2009596
3 2003181
4 2004118
5 2003101
6 202281
7 200273
8 202272
9 202159
10 202151
11 202144
12 202144
13 200642
14 201136
15 200635
16 202135
17 202031
18 202129
19 202415
20 200313

About Mary Wu

Mary Wu is a scholar working on Molecular Biology, Infectious Diseases, Epidemiology, Cell Biology and Cardiology and Cardiovascular Medicine, having authored 27 papers that have together received 2.8k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (7 papers), Autophagy in Disease and Therapy (5 papers), Viral gastroenteritis research and epidemiology (4 papers), Ubiquitin and proteasome pathways (3 papers), Endoplasmic Reticulum Stress and Disease (3 papers), Microtubule and mitosis dynamics (3 papers), Influenza Virus Research Studies (2 papers) and Cellular Mechanics and Interactions (2 papers). The work is most often cited by research in Aging (71 citations), Cancer Research (443 citations), Cell Biology (401 citations), Endocrinology (123 citations) and Molecular Biology (1.6k citations). Mary Wu has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Caroline S. Hill, Sally J. Leevers, Megan Cully, Thomas Porstmann, Yuen‐Li Chung, John R. Griffiths, B Griffiths, Almut Schulze, Cláudio R. Santos and Richard H. Kessin. Their work appears in journals such as Biochemical Journal, Nature Communications, Eukaryotic Cell, Journal of Biological Chemistry and Influenza and Other Respiratory Viruses.

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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