Kevin Gaida

3.2k total citations
9 papers, 185 citations indexed

About

Kevin Gaida is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Kevin Gaida has authored 9 papers receiving a total of 185 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Immunology and 4 papers in Oncology. Recurrent topics in Kevin Gaida's work include Cancer Treatment and Pharmacology (3 papers), Ion Channels and Receptors (3 papers) and Colorectal Cancer Treatments and Studies (2 papers). Kevin Gaida is often cited by papers focused on Cancer Treatment and Pharmacology (3 papers), Ion Channels and Receptors (3 papers) and Colorectal Cancer Treatments and Studies (2 papers). Kevin Gaida collaborates with scholars based in United States and Canada. Kevin Gaida's co-authors include Helen J. McBride, Raju Subramanian, Patrick J. Shaw, Ulrike Kaufmann, Lina Kozhaya, Stefan Feske, Derya Unutmaz, Shu-Yin Ho, Min Wong and Palaniswami Rathanaswami and has published in prestigious journals such as The Journal of Immunology, Cancer Research and Journal of Pharmacology and Experimental Therapeutics.

In The Last Decade

Kevin Gaida

7 papers receiving 177 citations

Peers

Kevin Gaida
Comparison fields: 5 of 40
  • Sensory Systems 81
  • Molecular Biology 77
  • Immunology 74
  • Oncology 34
  • Radiology, Nuclear Medicine and Imaging 33
Replace Shiyao Wu with:
Shiyao Wu China
Shuxian Zhou China
Oscar E. Reyes Gaido United States
Ilana B. Kotliar United States
Florence Blandel France
Jonathan Granger United States
Zhoumiao Chen China
Renny J. Starner United States
Jacob M. Winter United States
Bianca Esposito Italy
Shiyao Wu China View profile →
Citations per field, relative to Kevin Gaida
Kevin Gaida · 1×
Citations per year, relative to Kevin Gaida
Kevin Gaida · 1×

Countries citing papers authored by Kevin Gaida

Since Specialization
Citations

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

Fields of papers citing papers by Kevin Gaida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Gaida

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

All Works

9 of 9 papers shown
# Work Indexed citations
1 0
2 0
3 1
4 13
5
Development of an ICOSL and BAFF bispecific inhibitor AMG 570 for systemic lupus erythematosus treatment.
26
6 48
7 11
8 63
9 23

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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