Ruth Boxall

6 papers receiving 458 citations

Hit Papers

Lipids, Lipoproteins, and Metabolites and Risk of Myocardial Infarction and Stroke 2018 · 329 citations
3292018202620202023100200300

Peers

Ruth Boxall
Comparison fields: 5 of 85
  • Endocrinology, Diabetes and Metabolism 118
  • Cancer Research 81
  • Orthopedics and Sports Medicine 37
  • Cardiology and Cardiovascular Medicine 89
  • Biological Psychiatry 8
Replace Xiaoyang Lai with:
Xiaoyang Lai China
Asif Anwar United States
Kota Matsuki Japan
Weili Tang China
Maria Grazia Zenti Italy
Xiaojuan Bai China
Dalia El-Lebedy Egypt
Juan Wu China
Yukari Mimura Japan
K.-U. Lee South Korea
Ruth Boxall relative to Xiaoyang Lai China Xiaoyang Lai's profile →
Citations per field
00.5×3.7×
Xiaoyang Lai · 1×
Citations per year

Countries citing papers authored by Ruth Boxall

Since Specialization
Citations

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

Fields of papers citing papers by Ruth Boxall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Ruth Boxall, 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 Ruth Boxall Line = papers co-authored together Ruth Boxall links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 20233
2 202071
3
Lipids, Lipoproteins, and Metabolites and Risk of Myocardial Infarction and Stroke
Hit paper breakdown →
2018329
4
Serum NMR Metabolomics Identifies Similar Associations of Lipoproteins and Lipids With Risk of Myocardial Infarction and Ischemic Stroke but Not With Hemorrhagic Stroke
20160
5 201538
6 201113
7 19739

About Ruth Boxall

Ruth Boxall is a scholar working on Cancer Research, Orthopedics and Sports Medicine, Health, Toxicology and Mutagenesis, Nutrition and Dietetics and Endocrinology, Diabetes and Metabolism, having authored 7 papers that have together received 463 indexed citations. Recurring topics across this work include Metabolomics and Mass Spectrometry Studies (2 papers), Cancer, Lipids, and Metabolism (2 papers), Lipoproteins and Cardiovascular Health (2 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (1 paper), Genetic Associations and Epidemiology (1 paper), Vitamin C and Antioxidants Research (1 paper), RNA regulation and disease (1 paper) and Nutritional Studies and Diet (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (118 citations), Cancer Research (81 citations), Orthopedics and Sports Medicine (37 citations), Cardiology and Cardiovascular Medicine (89 citations) and Biological Psychiatry (8 citations). Ruth Boxall has collaborated with scholars based in United Kingdom, China and Australia. Frequent co-authors include Michael V. Holmes, Robin Walters, Liming Li, Zhengming Chen, Iona Y. Millwood, Michael Hill, Mika Ala‐Korpela, Sarah Parish, Canqing Yu and Christiana Kartsonaki. Their work appears in journals such as Journal of the American College of Cardiology, Science Translational Medicine, Journal of Psychiatric Research, Circulation and PLoS ONE.

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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