John Day

2.2k citations
53 papers · 1.8k · h-index 19

Impact in

Papers in

    • Protein Structure and Dynamics 12
    • Glycosylation and Glycoproteins Research 5
    • Enzyme Structure and Function 26
    • Crystallization and Solubility Studies 8

John Day

53 papers receiving 1.7k citations

Peers

John Day
Comparison fields: 5 of 109
  • Biotechnology 262
  • Structural Biology 24
  • Molecular Biology 1.0k
  • Materials Chemistry 518
  • Ecology 278
Replace Steven B. Larson with:
Steven B. Larson United States
A. C. Bloomer United Kingdom
J.D. Pédelacq France
Mirosława Dauter United States
Didier Nurizzo France
Véronique Receveur‐Brechot France
Hisao Yokota United States
Kristian Schweimer Germany
Alejandro Panjkovich Germany
Robert Seckler Germany
John Day relative to Steven B. Larson United States Steven B. Larson's profile →
Citations per field
00.5×1.5×
Steven B. Larson · 1×
Citations per year

Countries citing papers authored by John Day

Since Specialization
Citations

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

Fields of papers citing papers by John Day

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside John Day, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John Day Line = papers co-authored together John Day links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997236
2 1992157
3 1994140
4 1996101
5 199896
6 199486
7 199384
8 199479
9 198679
10 199263
11 199561
12 200360
13 201050
14 199947
15 200046
16 199742
17 200730
18 198620
19 199118
20 199116

About John Day

John Day is a scholar working on Molecular Biology, Materials Chemistry, Ecology, Plant Science and Radiology, Nuclear Medicine and Imaging, having authored 53 papers that have together received 1.8k indexed citations. Recurring topics across this work include Enzyme Structure and Function (26 papers), Bacteriophages and microbial interactions (12 papers), Protein Structure and Dynamics (12 papers), Plant Virus Research Studies (10 papers), Crystallization and Solubility Studies (8 papers), Enzyme Production and Characterization (8 papers), Monoclonal and Polyclonal Antibodies Research (8 papers) and Glycosylation and Glycoproteins Research (5 papers). The work is most often cited by research in Biotechnology (262 citations), Structural Biology (24 citations), Molecular Biology (1.0k citations), Materials Chemistry (518 citations) and Ecology (278 citations). John Day has collaborated with scholars based in United States, Taiwan and India. Frequent co-authors include Alexander McPherson, Steven B. Larson, Aaron Greenwood, Tzu‐Ping Ko, Duilio Cascio, Karl W. Hasel, Mary A. Canady, Robert Cudney, S. Koszelak and Lisa J. Harris. Their work appears in journals such as Journal of Molecular Biology, Acta Crystallographica Section B Structural Science, Biochemistry, Proteins Structure Function and Bioinformatics and Nature.

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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