Qi Da

580 citations
28 papers · 438 · h-index 10

Impact in

    • Cell Adhesion Molecules Research
  • Hematology top 10%
    • Platelet Disorders and Treatments
    • Blood Coagulation and Thrombosis Mechanisms

Papers in

    • Platelet Disorders and Treatments 12
    • Autoimmune and Inflammatory Disorders Research 2
    • Complement system in diseases 6

Qi Da

26 papers receiving 436 citations

Peers

Qi Da
Comparison fields: 5 of 93
  • Immunology and Allergy 51
  • Hematology 84
  • Immunology 108
  • Cell Biology 72
  • Internal Medicine 10
Replace F Maillet with:
F Maillet France
Imène Melki Canada
Keith Zientek United States
J Bayle France
Christine Choqueux France
Makogonenko Em United States
Philip M. Keegan United States
B. Scheuerer Germany
Ravi Kumar Alluri United States
Petra Vandervoort Belgium
Qi Da relative to F Maillet France F Maillet's profile →
Citations per field
00.5×10×20×30×37×
F Maillet · 1×
Citations per year

Countries citing papers authored by Qi Da

Since Specialization
Citations

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

Fields of papers citing papers by Qi Da

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201372
2 201570
3 200656
4 201848
5 201435
6 201833
7 201817
8 201413
9 201911
10 20209
11 20189
12 20119
13 20188
14 20168
15 20197
16 20226
17 20216
18 20165
19 20173
20 20163

About Qi Da

Qi Da is a scholar working on Hematology, Immunology, Immunology and Allergy, Molecular Biology and Mechanics of Materials, having authored 28 papers that have together received 438 indexed citations. Recurring topics across this work include Platelet Disorders and Treatments (12 papers), Complement system in diseases (6 papers), Cell Adhesion Molecules Research (6 papers), Rock Mechanics and Modeling (4 papers), Signaling Pathways in Disease (3 papers), Blood properties and coagulation (3 papers), Autoimmune and Inflammatory Disorders Research (2 papers) and Tunneling and Rock Mechanics (2 papers). The work is most often cited by research in Immunology and Allergy (51 citations), Hematology (84 citations), Immunology (108 citations), Cell Biology (72 citations) and Internal Medicine (10 citations). Qi Da has collaborated with scholars based in United States, China and Mexico. Frequent co-authors include Miguel A. Crúz, Fong Lam, Prasenjit Guchhait, John S. Olson, Jun Teruya, Bobby Guillory, K. Vinod Vijayan, Du Feng, Yang Zhang and B. Liu. Their work appears in journals such as Blood, Journal of Thrombosis and Haemostasis, Applied Sciences, The Journal of Immunology and Journal of Biological 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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