John Wu

1.7k citations
33 papers · 1.5k indexed · h-index 23

Impact in

    • DNA and Nucleic Acid Chemistry
    • Biochemical and Molecular Research
    • RNA and protein synthesis mechanisms
    • Genomics and Phylogenetic Studies
    • Glycosylation and Glycoproteins Research
    • Genomics and Chromatin Dynamics
    • Advanced biosensing and bioanalysis techniques

Papers in

John Wu

33 papers receiving 1.4k citations

Peers

John Wu
Comparison fields: 5 of 113
  • Transplantation 74
  • Molecular Biology 1.1k
  • Physiology 61
  • Clinical Biochemistry 62
  • Neurology 62
Replace Benoı̂t Pinson with:
Benoı̂t Pinson France
Shuhong Hu China
Benjamin Clémençon Switzerland
Xuemei Han China
Srinivas Ayyadevara United States
Michelle E. Kimple United States
Piero Luigi Ipata Italy
Alessandro Magini Italy
Hisao Ueyama Japan
Gary M. Jenkins United States
John Wu relative to Benoı̂t Pinson France Benoı̂t Pinson's profile →
Citations per field
00.5×5.7×
Benoı̂t Pinson · 1×
Citations per year

Countries citing papers authored by John Wu

Since Specialization
Citations

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

Fields of papers citing papers by John Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1980204
2 1978162
3
Primate brain maps : structure of the macaque brain
2000136
4 198895
5 199494
6 198581
7 200979
8 198873
9 201055
10 199545
11 199641
12 199440
13 200835
14 201834
15 201733
16 198532
17 200925
18 198125
19 198824
20 199523

About John Wu

John Wu is a scholar working on Transplantation, Physiology, Process Chemistry and Technology, Molecular Biology and Emergency Medicine, having authored 33 papers that have together received 1.5k indexed citations. Recurring topics across this work include Biochemical and Molecular Research (7 papers), DNA and Nucleic Acid Chemistry (5 papers), Neonatal Health and Biochemistry (4 papers), Protist diversity and phylogeny (3 papers), Adenosine and Purinergic Signaling (3 papers), Traumatic Brain Injury Research (3 papers), HIV/AIDS drug development and treatment (3 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). The work is most often cited by research in Transplantation (74 citations), Molecular Biology (1.1k citations), Physiology (61 citations), Clinical Biochemistry (62 citations) and Neurology (62 citations). John Wu has collaborated with scholars based in United States, Taiwan and Canada. Frequent co-authors include Laura Manuelidis, John W. Kozarich, JoAnne Stubbe, Daniel V. Santi, Richard Martin, Mark Dubach, Kenneth Straub, Douglas M. Bowden, Ken F. Jarrell and Shin‐Ichi Aizawa. Their work appears in journals such as Biochemistry, Journal of Bacteriology, Brain Research, International Journal of Molecular Sciences and Journal of Medicinal Chemistry.

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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