M. O. Dayhoff

14.2k citations
71 papers · 11.6k indexed · 5 hit papers · h-index 32
Topics
Genomics and Phylogenetic Studies (13 papers)RNA and protein synthesis mechanisms (11 papers)Machine Learning in Bioinformatics (10 papers)
Partner nations
United StatesAustralia

In The Last Decade

M. O. Dayhoff

69 papers receiving 10.9k citations

Hit Papers

Atlas of protein sequence and structure19652026198520051965197319671983197810002.0k3.0k

Peers

M. O. Dayhoff
Comparison fields: 5 of 176
  • Molecular Biology 7.9k
  • Genetics 1.7k
  • Cell Biology 1.1k
  • Plant Science 1000
  • Ecology 971
Replace Karl Schmid with:
Karl Schmid United States
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Sung‐Hou Kim United States
Keiichi Itakura United States
Arthur M. Lesk United Kingdom
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Patrick Argos Germany
Morten Kjeldgaard Denmark
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Jack Kyte United States
M. O. Dayhoff relative to Karl Schmid United States Karl Schmid's profile →
Citations per field
00.5×2.9×
Karl Schmid · 1×
Citations per year

Countries citing papers authored by M. O. Dayhoff

Since Specialization
Citations

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

Fields of papers citing papers by M. O. Dayhoff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. O. Dayhoff

This figure shows the co-authorship network connecting the top 25 collaborators of M. O. Dayhoff. A scholar is included among the top collaborators of M. O. Dayhoff 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 M. O. Dayhoff. M. O. Dayhoff 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 1
2
[47] Establishing homologies in protein sequencesbreakdown →
1050
3 42
4 6
5 2
6 18
7 51
8 22
9 33
10 7
11 10
12
A model of evolutionary change in protein
123
13 73
14 8
15 50
16 5
17 16
18 6
19 70
20 2

About M. O. Dayhoff

M. O. Dayhoff is a scholar working on Filtration and Separation, Molecular Biology and Astronomy and Astrophysics, having authored 71 papers that have together received 11.6k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (13 papers), RNA and protein synthesis mechanisms (11 papers) and Machine Learning in Bioinformatics (10 papers). The work is most often cited by research in Molecular Biology (7.9k citations), Cell Biology (1.1k citations) and Genetics (1.7k citations). M. O. Dayhoff has collaborated with scholars based in United States and Australia. Frequent co-authors include Richard V. Eck, Walter M. Fitch, Min-Yen Chang, Lois T. Hunt, Winona C. Barker, R.T. Hersh, R. M. Schwartz, Ellis R. Lippincott, D. A. MacInnes and B.C. ORCUTT. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.

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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