Joanna M. Day

1.1k citations
27 papers · 972 indexed · h-index 18
Topics
Estrogen and related hormone effects (18 papers)Hormonal Regulation and Hypertension (9 papers)Pharmacogenetics and Drug Metabolism (7 papers)

In The Last Decade

Joanna M. Day

27 papers receiving 954 citations

Peers

Joanna M. Day
Comparison fields: 5 of 81
  • Genetics 501
  • Molecular Biology 449
  • Endocrinology, Diabetes and Metabolism 309
  • Organic Chemistry 162
  • Cell Biology 140
Replace Surinder K. Chander with:
Surinder K. Chander United Kingdom
Martin R. Schneider Germany
Simon P. Newman United Kingdom
Rosemary E. Hall Australia
Venkatesh Handratta United States
Surojeet Sengupta United States
Steven Sugarman United States
Alexander Yemelyanov United States
Hing-Yat Peter Lam Canada
René Maltais Canada
Joanna M. Day relative to Surinder K. Chander United Kingdom Surinder K. Chander's profile →
Citations per field
00.5×1.6×
Surinder K. Chander · 1×
Citations per year

Countries citing papers authored by Joanna M. Day

Since Specialization
Citations

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

Fields of papers citing papers by Joanna M. Day

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joanna M. Day

This figure shows the co-authorship network connecting the top 25 collaborators of Joanna M. Day. A scholar is included among the top collaborators of Joanna M. Day 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 Joanna M. Day. Joanna M. Day 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 19
2 62
3 12
4 18
5 34
6 103
7 100
8 38
9 25
10 14
11 7
12 25
13 4
14 37
15 22
16 31
17 9
18 30
19 14
20 80

About Joanna M. Day

Joanna M. Day is a scholar working on Pharmacology, Genetics and Endocrinology, Diabetes and Metabolism, having authored 27 papers that have together received 972 indexed citations. Recurring topics across this work include Estrogen and related hormone effects (18 papers), Hormonal Regulation and Hypertension (9 papers) and Pharmacogenetics and Drug Metabolism (7 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (309 citations), Genetics (501 citations) and Toxicology (44 citations). Joanna M. Day has collaborated with scholars based in United Kingdom, France and Netherlands. Frequent co-authors include Helena J. Tutill, Michael Reed, Atul Purohit, Barry V. L. Potter, A. Purohit, Nigel Vicker, Simon P. Newman, Paul Foster, Matthew J. Reed and Harshani R. Lawrence. Their work appears in journals such as Journal of Biological Chemistry, PLoS ONE and The Journal of Clinical Endocrinology & Metabolism.

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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