Benoît Tyl

2.7k citations
28 papers · 874 · 1 hit paper · h-index 14

Impact in

Papers in

Benoît Tyl

27 papers receiving 851 citations

Benoît Tyl's Hit Papers

Genetic drug target validation using Mendelian randomisation 2020 · 291 citations
2910+2+4Years since publication50100150200250

Peers

Benoît Tyl
Comparison fields: 5 of 107
  • Health Informatics 21
  • Cardiology and Cardiovascular Medicine 212
  • Immunology and Allergy 37
  • Genetics 128
  • Rheumatology 46
Replace R Thomas Lumbers with:
R Thomas Lumbers United Kingdom
Julian R. Homburger United States
Lisa A. Bastarache United States
M. Khair ElZarrad United States
Gregory F. Guzauskas United States
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Debbie Chen United States
Wendy A. Wolf United States
Hidetoshi Matsuo Japan
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Citations per field
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Citations per year

Countries citing papers authored by Benoît Tyl

Since Specialization
Citations

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

Fields of papers citing papers by Benoît Tyl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Genetic drug target validation using Mendelian randomisation
Hit paper breakdown →
2020291
2 2019186
3 201553
4 201149
5 200734
6 202334
7 202233
8 201226
9 201823
10 202022
11 201021
12 202121
13 200918
14 202116
15 202213
16 20219
17 20087
18 20205
19 20242
20 20242

About Benoît Tyl

Benoît Tyl is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology, Epidemiology, Nephrology and Radiology, Nuclear Medicine and Imaging, having authored 28 papers that have together received 874 indexed citations. Recurring topics across this work include Cardiac electrophysiology and arrhythmias (6 papers), Cardiovascular Function and Risk Factors (4 papers), Heart Failure Treatment and Management (3 papers), Chronic Kidney Disease and Diabetes (2 papers), Atrial Fibrillation Management and Outcomes (2 papers), ECG Monitoring and Analysis (2 papers), Chronic Disease Management Strategies (1 paper) and Healthcare Systems and Public Health (1 paper). The work is most often cited by research in Health Informatics (21 citations), Cardiology and Cardiovascular Medicine (212 citations), Immunology and Allergy (37 citations), Genetics (128 citations) and Rheumatology (46 citations). Benoît Tyl has collaborated with scholars based in France, Germany and United States. Frequent co-authors include Amitava Banerjee, Menno Mostert, Shona Kalkman, Ghislaine J. M. W. van Thiel, Johannes van Delden, Folkert W. Asselbergs, Amand F. Schmidt, Sandesh Chopade, Riyaz Patel and María Gordillo‐Marañón. Their work appears in journals such as The Journal of Clinical Pharmacology, European Heart Journal, Nature Communications, European Journal of Heart Failure and Heart Rhythm.

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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