Pingping Guan

1.2k citations
17 papers · 1.0k · h-index 14

Impact in

Papers in

    • vaccines and immunoinformatics approaches 15
    • Machine Learning in Bioinformatics 1
    • RNA and protein synthesis mechanisms 1
    • Immunotherapy and Immune Responses 9
    • T-cell and B-cell Immunology 7
    • Immune Cell Function and Interaction 1

Pingping Guan

17 papers receiving 981 citations

Peers

Pingping Guan
Comparison fields: 5 of 68
  • Immunology 452
  • Radiology, Nuclear Medicine and Imaging 381
  • Molecular Biology 870
  • Microbiology 59
  • Biotechnology 67
Replace Pernille Andersen with:
Pernille Andersen Denmark
Elodie Foulquier France
Peter Schoofs Australia
Kamilla Kjærgaard Jensen Denmark
Michael Rasmussen Denmark
Tiziana Sturniolo Italy
Magdalena Blaszczyk‐Thurin United States
Marie‐Madeleine Riottot France
Birkir Reynisson Argentina
Bruno Alvarez Argentina
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Citations per field
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Citations per year

Countries citing papers authored by Pingping Guan

Since Specialization
Citations

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

Fields of papers citing papers by Pingping Guan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Pingping Guan, 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 Pingping Guan Line = papers co-authored together Pingping Guan links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2003222
2 2005144
3 2006140
4 200495
5 200669
6
MHCPred: bringing a quantitative dimension to the online prediction of MHC binding.
200362
7 200344
8 200942
9 200542
10 200338
11 200428
12 200518
13 200317
14 200416
15 200313
16 200710
17 20071

About Pingping Guan

Pingping Guan is a scholar working on Molecular Biology, Immunology, Radiology, Nuclear Medicine and Imaging, Cellular and Molecular Neuroscience and Cell Biology, having authored 17 papers that have together received 1.0k indexed citations. Recurring topics across this work include vaccines and immunoinformatics approaches (15 papers), Monoclonal and Polyclonal Antibodies Research (9 papers), Immunotherapy and Immune Responses (9 papers), T-cell and B-cell Immunology (7 papers), Neurobiology and Insect Physiology Research (1 paper), Machine Learning in Bioinformatics (1 paper), Immune Cell Function and Interaction (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Immunology (452 citations), Radiology, Nuclear Medicine and Imaging (381 citations), Molecular Biology (870 citations), Microbiology (59 citations) and Biotechnology (67 citations). Pingping Guan has collaborated with scholars based in United Kingdom and Bulgaria. Frequent co-authors include Irini Doytchinova, Darren R. Flower, Channa K. Hattotuwagama, Christopher P. Toseland, Martin Blythe, Persephone Borrow, Robert A. Field, Richard J. Morris, Carla García‐Morales and Mark Fidock. Their work appears in journals such as BMC Bioinformatics, Journal of Molecular Graphics and Modelling, Expert Opinion on Drug Discovery, Organic & Biomolecular Chemistry and Methods.

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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