Gang Wu

30.5k total citations · 1 hit paper
151 papers, 4.7k citations indexed

About

Gang Wu is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Gang Wu has authored 151 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 94 papers in Molecular Biology, 28 papers in Cancer Research and 17 papers in Genetics. Recurrent topics in Gang Wu's work include Genomics and Phylogenetic Studies (15 papers), Epigenetics and DNA Methylation (15 papers) and Cancer Genomics and Diagnostics (14 papers). Gang Wu is often cited by papers focused on Genomics and Phylogenetic Studies (15 papers), Epigenetics and DNA Methylation (15 papers) and Cancer Genomics and Diagnostics (14 papers). Gang Wu collaborates with scholars based in United States, China and United Kingdom. Gang Wu's co-authors include Weiwen Zhang, Lei Nie, Jinghui Zhang, David Culley, Qiang Yan, Yinjie Tang, Stephen S. Fong, Mattheos Koffas, J. Andrew Jones and Johannes C. M. Scholten and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Gang Wu

143 papers receiving 4.6k citations

Hit Papers

Metabolic Burden: Cornerstones in Synthetic Biology and M... 2016 2026 2019 2022 2016 100 200 300 400

Peers

Gang Wu
Comparison fields: 5 of 154
  • Molecular Biology 3.0k
  • Genetics 552
  • Immunology 521
  • Cancer Research 520
  • Oncology 483
Replace Shu‐Wha Lin with:
Shu‐Wha Lin Taiwan
Michael T. Overgaard Denmark
Weijun Luo United States
Yong‐Dong Wang United States
Daniel Swan United Kingdom
Francesco Costanzo Italy
Martin Granzow Germany
Ajay A. Vashisht United States
Robert H. Rice United States
Shu‐Wha Lin Taiwan View profile →
Citations per field, relative to Gang Wu
Gang Wu · 1×
Citations per year, relative to Gang Wu
Gang Wu · 1×

Countries citing papers authored by Gang Wu

Since Specialization
Citations

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

Fields of papers citing papers by Gang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gang Wu

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 2
2 0
3 5
4 2
5 1
6 7
7 43
8 0
9 1
10 12
11 6
12 5
13 9
14 9
15 27
16 17
17 16
18 36
19 18
20
Genomic variation of the rice {\sl Rim2/Hipa} superfamily and dendrogram and fingerprinting analysis of rice germplasm based on {\sl Rim2/Hipa} paralog display
1

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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