Kaiyu Wu

1.3k total citations · 1 hit paper
13 papers, 1.1k citations indexed

About

Kaiyu Wu is a scholar working on Infectious Diseases, Molecular Biology and Gastroenterology. According to data from OpenAlex, Kaiyu Wu has authored 13 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Infectious Diseases, 7 papers in Molecular Biology and 4 papers in Gastroenterology. Recurrent topics in Kaiyu Wu's work include Antimicrobial Resistance in Staphylococcus (6 papers), Gastrointestinal motility and disorders (4 papers) and Bacterial biofilms and quorum sensing (4 papers). Kaiyu Wu is often cited by papers focused on Antimicrobial Resistance in Staphylococcus (6 papers), Gastrointestinal motility and disorders (4 papers) and Bacterial biofilms and quorum sensing (4 papers). Kaiyu Wu collaborates with scholars based in Canada, China and United States. Kaiyu Wu's co-authors include Kunyan Zhang, John Conly, Björn Petri, Bryan G. Yipp, Craig N. Jenne, Brittney Scott, Stephen E. Malawista, Davide Salina, Lori Zbytnuik and Keir Pittman and has published in prestigious journals such as Nature Medicine, Clinical Infectious Diseases and Journal of Bacteriology.

In The Last Decade

Kaiyu Wu

13 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Infection-induced NETosis is a dynamic process involving neutrophil multitasking in vivo

2012 901 citations Bryan G. Yipp, Björn Petri et al. Nature Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Kaiyu Wu Canada	9	807	350	185	130	117	13	1.1k
Karen Poon Canada	6	808 1.0×	344 1.0×	137 0.7×	149 1.1×	101 0.9×	6	1.0k
Florian H. Pilsczek United States	7	804 1.0×	282 0.8×	120 0.6×	150 1.2×	98 0.8×	17	981
Emma K. Persson Sweden	14	1.4k 1.7×	355 1.0×	152 0.8×	93 0.7×	180 1.5×	18	2.0k
Aoi Akitsu Japan	9	882 1.1×	240 0.7×	155 0.8×	38 0.3×	115 1.0×	16	1.2k
April Clark United States	8	637 0.8×	726 2.1×	101 0.5×	66 0.5×	116 1.0×	10	1.2k
Liz M. Lavigne United States	9	420 0.5×	192 0.5×	201 1.1×	78 0.6×	165 1.4×	12	745
Thomas W. Spahn Germany	15	566 0.7×	135 0.4×	75 0.4×	57 0.4×	95 0.8×	24	907
Elin Jaensson Gyllenbäck Sweden	12	1.2k 1.5×	367 1.0×	100 0.5×	36 0.3×	101 0.9×	19	1.6k
Lucas Thompson United States	12	1.0k 1.3×	264 0.8×	168 0.9×	34 0.3×	194 1.7×	19	1.6k
Friederike Hug Germany	19	524 0.6×	232 0.7×	47 0.3×	90 0.7×	105 0.9×	22	933

Countries citing papers authored by Kaiyu Wu

Since Specialization

Citations

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

Fields of papers citing papers by Kaiyu Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kaiyu Wu

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

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

Conly, John, Jo‐Ann McClure, Kaiyu Wu, et al.. (2021). A Murine Skin Infection Model Capable of Differentiating the Dermatopathology of Community-Associated MRSA Strain USA300 from Other MRSA Strains. Microorganisms. 9(2). 287–287. 5 indexed citations

Wu, Kaiyu, John Conly, Jo‐Ann McClure, Habib A. Kurwa, & Kunyan Zhang. (2020). Arginine Catabolic Mobile Element in Evolution and Pathogenicity of the Community-Associated Methicillin-Resistant Staphylococcus aureus Strain USA300. Microorganisms. 8(2). 275–275. 14 indexed citations

Cannon, Kristine, Brendan Byrne, Kaiyu Wu, et al.. (2017). Enteric microbiome profiles during a randomized Phase 2 clinical trial of surotomycin versus vancomycin for the treatment of Clostridium difficile infection. Journal of Antimicrobial Chemotherapy. 72(12). 3453–3461. 19 indexed citations

Ward, Linda, et al.. (2016). Combined Oral Fecal Capsules Plus Fecal Enema as Treatment of Late-Onset Autism Spectrum Disorder in Children: Report of a Small Case Series. Open Forum Infectious Diseases. 3(suppl_1). 10 indexed citations

Louie, Thomas, Brendan Byrne, Jordan Fraser Emery, et al.. (2015). Differences of the Fecal Microflora With Clostridium difficile Therapies. Clinical Infectious Diseases. 60(suppl 2). S91–S97. 23 indexed citations

Wu, Kaiyu, et al.. (2015). Impact of Ascending Dosages of Cadazolid or Vancomycin on the Intestinal Microbiome During Treatment of Clostridium difficile Infection. Open Forum Infectious Diseases. 2(suppl_1). 1 indexed citations

Wu, Kaiyu, Kunyan Zhang, Jo‐Ann McClure, et al.. (2012). A correlative analysis of epidemiologic and molecular characteristics of methicillin-resistant Staphylococcus aureus clones from diverse geographic locations with virulence measured by a Caenorhabditis elegans host model. European Journal of Clinical Microbiology & Infectious Diseases. 32(1). 33–42. 8 indexed citations

Wu, Kaiyu, John Conly, Michael G. Surette, et al.. (2012). Assessment of virulence diversity of methicillin-resistant Staphylococcus aureus strains with a Drosophila melanogaster infection model. BMC Microbiology. 12(1). 274–274. 19 indexed citations

Yipp, Bryan G., Björn Petri, Davide Salina, et al.. (2012). Infection-induced NETosis is a dynamic process involving neutrophil multitasking in vivo. Nature Medicine. 18(9). 1386–1393. 901 indexed citations breakdown →

10.

Wu, Kaiyu, Andrew E. Simor, Mary Vearncombe, Jo‐Ann McClure, & Kunyan Zhang. (2012). A Caenorhabditis elegans Host Model Correlates with Invasive Disease Caused by Staphylococcus aureus Recovered during an Outbreak in Neonatal Intensive Care. Canadian Journal of Infectious Diseases and Medical Microbiology. 23(3). 130–134. 10 indexed citations

11.

Wu, Kaiyu, John Conly, Jo‐Ann McClure, et al.. (2009). Caenorhabditis elegans as a host model for community-associated methicillin-resistant Staphylococcus aureus. Clinical Microbiology and Infection. 16(3). 245–254. 32 indexed citations

12.

Wu, Kaiyu. (2009). Determination of Ca in a High P/Ca Liquid Compound Fertilizer. 1 indexed citations

13.

Wu, Kaiyu, Gui‐Rong Liu, Weiqiao Liu, et al.. (2005). The Genome of Salmonella enterica Serovar Gallinarum: Distinct Insertions/Deletions and Rare Rearrangements. Journal of Bacteriology. 187(14). 4720–4727. 22 indexed citations

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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