J. Slack

1.5k citations
16 papers · 1.1k indexed · h-index 11

Impact in

Papers in

J. Slack

16 papers receiving 1.1k citations

Peers

J. Slack
Comparison fields: 5 of 99
  • Genetics 233
  • Endocrinology, Diabetes and Metabolism 308
  • Cancer Research 178
  • Cardiology and Cardiovascular Medicine 235
  • Pulmonary and Respiratory Medicine 244
Replace Jan Willem N. Akkerman with:
Jan Willem N. Akkerman Netherlands
N Ardaillou France
Alain Rupin France
R W Colman United States
Kazuhiro Miwa Japan
Brigitte Kaiser Germany
Bruce Lages United States
Iris Müller Germany
Min Ren United States
Klaus Baumann Germany
J. Slack relative to Jan Willem N. Akkerman Netherlands Jan Willem N. Akkerman's profile →
Citations per field
00.5×2.9×
Jan Willem N. Akkerman · 1×
Citations per year

Countries citing papers authored by J. Slack

Since Specialization
Citations

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

Fields of papers citing papers by J. Slack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

16 of 16 papers shown
#Work
1 1992398
2 19836
3 19829
4 198214
5 198191
6 19815
7 19801
8 19802
9 197743
10 197747
11 197753
12 1977178
13 197115
14 196821
15 196839
16 1966221

About J. Slack

J. Slack is a scholar working on Nephrology, Endocrinology, Diabetes and Metabolism, Surgery, Clinical Biochemistry and Cardiology and Cardiovascular Medicine, having authored 16 papers that have together received 1.1k indexed citations. Recurring topics across this work include Lipoproteins and Cardiovascular Health (8 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (5 papers), Lipid metabolism and disorders (3 papers), Gout, Hyperuricemia, Uric Acid (3 papers), Cholesterol and Lipid Metabolism (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Nutrition, Genetics, and Disease (1 paper) and Blood properties and coagulation (1 paper). The work is most often cited by research in Genetics (233 citations), Endocrinology, Diabetes and Metabolism (308 citations), Cancer Research (178 citations), Cardiology and Cardiovascular Medicine (235 citations) and Pulmonary and Respiratory Medicine (244 citations). J. Slack has collaborated with scholars based in United Kingdom, India and United States. Frequent co-authors include K. Evans, ES Newlands, Ronald Hoffman, Alan Barnes, Peter Locke, P R Scudder, T. L. Dormandy, John Dormandy, N C Nevin and Arvid Heiberg. Their work appears in journals such as Journal of Medical Genetics, Annals of the Rheumatic Diseases, The Lancet, British Journal of Cancer and Advances in experimental medicine and biology.

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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