Hannah Wang

1.8k citations
21 papers · 737 · h-index 13

Impact in

Papers in

Hannah Wang

19 papers receiving 703 citations

Peers

Hannah Wang
Comparison fields: 5 of 118
  • Dermatology 60
  • Behavioral Neuroscience 22
  • Oncology 162
  • Biological Psychiatry 13
  • Molecular Biology 377
Replace Cheryl Allen with:
Cheryl Allen United States
Caiyun Liu China
Jennifer Kim United States
Christian Schmidt Germany
Kyung-Ah Kim South Korea
Ivan Fernández‐Vega Spain
Man Jiang China
Harald König Germany
Lin Han China
Junwei Huang China
Hannah Wang relative to Cheryl Allen United States Cheryl Allen's profile →
Citations per field
00.5×10×
Cheryl Allen · 1×
Citations per year

Countries citing papers authored by Hannah Wang

Since Specialization
Citations

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

Fields of papers citing papers by Hannah Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hannah Wang, 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 Hannah Wang Line = papers co-authored together Hannah Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017154
2 2003120
3 2017106
4 2011105
5 200340
6 199837
7 201927
8 200426
9 201126
10 199925
11 201320
12 200113
13 202112
14 20039
15 20228
16 20193
17 20202
18 19992
19 20021
20 20151

About Hannah Wang

Hannah Wang is a scholar working on Molecular Biology, Electrical and Electronic Engineering, Cellular and Molecular Neuroscience, Oncology and Computational Mechanics, having authored 21 papers that have together received 737 indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (4 papers), Ubiquitin and proteasome pathways (3 papers), Semiconductor materials and devices (2 papers), Histone Deacetylase Inhibitors Research (2 papers), Multiple Myeloma Research and Treatments (2 papers), Customer Service Quality and Loyalty (2 papers), Neurogenesis and neuroplasticity mechanisms (1 paper) and Organic Electronics and Photovoltaics (1 paper). The work is most often cited by research in Dermatology (60 citations), Behavioral Neuroscience (22 citations), Oncology (162 citations), Biological Psychiatry (13 citations) and Molecular Biology (377 citations). Hannah Wang has collaborated with scholars based in Singapore, United States and United Kingdom. Frequent co-authors include John Caldwell, Ian Collins, Raj Chopra, Min Xie, H.P. Lee, Kee Seng Chia, David Koh, Chee Leok Goh, J. Lee and Charis Eng. Their work appears in journals such as Journal of Information Science, British Journal of Dermatology, Oxidative Medicine and Cellular Longevity, Blood and Thin Solid Films.

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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