Kayla M. Peck

967 citations
13 papers · 636 indexed · 1 hit paper · h-index 9
Topics
SARS-CoV-2 and COVID-19 Research (5 papers)Evolution and Genetic Dynamics (5 papers)Peptidase Inhibition and Analysis (3 papers)

In The Last Decade

Kayla M. Peck

13 papers receiving 626 citations

Hit Papers

Complexities of Viral Mutation Rates2018202620202023201850100150200250

Peers

Kayla M. Peck
Comparison fields: 5 of 72
  • Infectious Diseases 436
  • Molecular Biology 153
  • Animal Science and Zoology 135
  • Public Health, Environmental and Occupational Health 117
  • Epidemiology 89
Replace Chan-Ki Min with:
Chan-Ki Min South Korea
Charles B. Stauft United States
Fanli Yang China
Jonathan O. Rayner United States
Ming Te Yeh United States
Nicolás Cifuentes-Muñoz Chile
Quanshui Fan China
George Carnell United Kingdom
Andrew S. Kondratowicz United States
Majid Laassri United States
Kayla M. Peck relative to Chan-Ki Min South Korea Chan-Ki Min's profile →
Citations per field
00.5×2.6×
Chan-Ki Min · 1×
Citations per year

Countries citing papers authored by Kayla M. Peck

Since Specialization
Citations

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

Fields of papers citing papers by Kayla M. Peck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kayla M. Peck. 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 Kayla M. Peck. The network helps show where Kayla M. Peck may publish in the future.

Co-authorship network of co-authors of Kayla M. Peck

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

All Works

13 of 13 papers shown
#WorkIndexed citations
1 4
2 1
3
Complexities of Viral Mutation Ratesbreakdown →
271
4 53
5 37
6 30
7 18
8 53
9 9
10 67
11 2
12 83
13 8

About Kayla M. Peck

Kayla M. Peck is a scholar working on Infectious Diseases, Animal Science and Zoology and Genetics, having authored 13 papers that have together received 636 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (5 papers), Evolution and Genetic Dynamics (5 papers) and Peptidase Inhibition and Analysis (3 papers). The work is most often cited by research in Infectious Diseases (436 citations), Animal Science and Zoology (135 citations) and Modeling and Simulation (31 citations). Kayla M. Peck has collaborated with scholars based in United States, Australia and Austria. Frequent co-authors include Adam S. Lauring, Mark T. Heise, Ralph S. Baric, Christina L. Burch, Trevor Scobey, Boyd L. Yount, Adam S. Cockrell, Sudhakar Agnihothram, Jesica Swanstrom and Kara Jensen. Their work appears in journals such as PLoS ONE, Cancer Research and Journal of Virology.

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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