Winona C. Barker

5.6k citations
55 papers · 3.7k indexed · 1 hit paper · h-index 29
Topics
Genomics and Phylogenetic Studies (20 papers)Machine Learning in Bioinformatics (12 papers)Glycosylation and Glycoproteins Research (9 papers)

In The Last Decade

Winona C. Barker

55 papers receiving 3.5k citations

Hit Papers

[47] Establishing homologies in protein sequences198320261997201119832505007501000

Peers

Winona C. Barker
Comparison fields: 5 of 130
  • Molecular Biology 2.7k
  • Genetics 514
  • Immunology 309
  • Plant Science 305
  • Materials Chemistry 268
Replace Lois T. Hunt with:
Lois T. Hunt United States
M.S. Nissen United States
Mike Carson United States
Radomir Crkvenjakov United States
J. Garnier France
G. F. Hong United Kingdom
Rainer Fuchs Germany
Raymond Reeves United States
Richard Blevins United States
Mark O. J. Olson United States
Winona C. Barker relative to Lois T. Hunt United States Lois T. Hunt's profile →
Citations per field
00.5×1.5×2.5×
Lois T. Hunt · 1×
Citations per year

Countries citing papers authored by Winona C. Barker

Since Specialization
Citations

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

Fields of papers citing papers by Winona C. Barker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Winona C. Barker. 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 Winona C. Barker. The network helps show where Winona C. Barker may publish in the future.

Co-authorship network of co-authors of Winona C. Barker

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 88
2 13
3 77
4 87
5 139
6 29
7 123
8 20
9 60
10 55
11 17
12 32
13 1
14 15
15 2
16 12
17 48
18 24
19
[47] Establishing homologies in protein sequencesbreakdown →
1050
20 10

About Winona C. Barker

Winona C. Barker is a scholar working on Molecular Biology, Biotechnology and Cell Biology, having authored 55 papers that have together received 3.7k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (20 papers), Machine Learning in Bioinformatics (12 papers) and Glycosylation and Glycoproteins Research (9 papers). The work is most often cited by research in Molecular Biology (2.7k citations), Virology (108 citations) and Genetics (514 citations). Winona C. Barker has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include Lois T. Hunt, M. O. Dayhoff, Cathy Wu, David G. George, Hongzhan Huang, Lai-Su Yeh, D. G. George, A. N. NIKOL'SKAYA, Cecilia N. Arighi and John S. Garavelli. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

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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