Dianbo Qu

1.4k citations
33 papers · 1.1k indexed · h-index 18

Impact in

Papers in

Dianbo Qu

32 papers receiving 1.1k citations

Peers

Dianbo Qu
Comparison fields: 5 of 88
  • Neurology 248
  • Neurology 106
  • Cell Biology 206
  • Cellular and Molecular Neuroscience 219
  • Developmental Neuroscience 45
Replace Shlomit Erlich with:
Shlomit Erlich Israel
Samantha H. Y. Loh United Kingdom
Jack C. Reidling United States
Eleanna Stamatakou United Kingdom
Diego Grassi United States
Michael Kurnellas United States
Kahori Shiba‐Fukushima Japan
Yasunari Munemasa Japan
Deepa V. Dabir United States
Brett A. McCray United States
Dianbo Qu relative to Shlomit Erlich Israel Shlomit Erlich's profile →
Citations per field
00.5×2.8×
Shlomit Erlich · 1×
Citations per year

Countries citing papers authored by Dianbo Qu

Since Specialization
Citations

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

Fields of papers citing papers by Dianbo Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 20242
3 20241
4 20231
5 20226
6 201932
7 201939
8 201910
9 201554
10 201264
11 201097
12 200963
13 200917
14 200731
15 2007207
16
Influence of ica operon transcription on clinical Staphylococcus epidermidis biofilm phenotype
20061
17 200646
18 200648
19 200326
20 200257

About Dianbo Qu

Dianbo Qu is a scholar working on Microbiology, Neurology, Cellular and Molecular Neuroscience, Cell Biology and Molecular Biology, having authored 33 papers that have together received 1.1k indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (8 papers), Cancer-related Molecular Pathways (5 papers), Genomics and Chromatin Dynamics (4 papers), Genetics and Neurodevelopmental Disorders (4 papers), RNA Research and Splicing (3 papers), RNA regulation and disease (3 papers), DNA Repair Mechanisms (3 papers) and Neuroscience and Neuropharmacology Research (3 papers). The work is most often cited by research in Neurology (248 citations), Neurology (106 citations), Cell Biology (206 citations), Cellular and Molecular Neuroscience (219 citations) and Developmental Neuroscience (45 citations). Dianbo Qu has collaborated with scholars based in Canada, China and United States. Frequent co-authors include David S. Park, Ruth S. Slack, Maxime W.C. Rousseaux, Steve Callaghan, John Woulfe, En Huang, Robert Z. Qi, Daniel Figeys, Hossein Aleyasin and Juliet Rashidian. Their work appears in journals such as Journal of Biological Chemistry, Journal of Neuroscience, Journal of Neurochemistry, BMC Biology and Aging.

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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