Antoine Lizée
Impact in
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- Computational Drug Discovery Methods
- Pathology and Forensic Medicine top 10%
- Multiple Sclerosis Research Studies
Papers in
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- Multiple Sclerosis Research Studies 6
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- Systemic Lupus Erythematosus Research 4
- Rheumatoid Arthritis Research and Therapies 1
- Co-authors
- Pouya Khankhanian (3 shared papers)Sergio E. Baranzini (3 shared papers)Daniel Himmelstein (2 shared papers)Sabrina Chen (1 shared paper)Dexter Hadley (1 shared paper)Leo Brueggeman (1 shared paper)Ari Green (2 shared papers)Christine Hessler (1 shared paper)
- Journals
- The Pharmacogenomics Journal (1 paper)Neurology (1 paper)eLife (1 paper)Journal of Medical Internet Research (1 paper)Journal of Neurology (1 paper)
- Partner nations
- United StatesFranceAustralia
In The Last Decade
Antoine Lizée
8 papers receiving 531 citations
Peers
Comparison fields: 5 of 93
- Computational Theory and Mathematics 145
- Pathology and Forensic Medicine 123
- Health Informatics 6
- Molecular Biology 269
- Immunology 67
Countries citing papers authored by Antoine Lizée
This map shows the geographic impact of Antoine Lizée'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 Antoine Lizée with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antoine Lizée more than expected).
Fields of papers citing papers by Antoine Lizée
This network shows the impact of papers produced by Antoine Lizée. 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 Antoine Lizée. The network helps show where Antoine Lizée may publish in the future.
Co-authors
The 25 scholars most cited alongside Antoine Lizée, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 305 | |
| 2 | 2016 | 106 | |
| 3 | 2016 | 53 | |
| 4 | 2017 | 26 | |
| 5 | 2020 | 22 | |
| 6 | 2015 | 17 | |
| 7 | 2015 | 11 | |
| 8 | 2017 | 1 |
About Antoine Lizée
Antoine Lizée is a scholar working on Pathology and Forensic Medicine, Rheumatology, Immunology, Molecular Biology and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 541 indexed citations. Recurring topics across this work include Multiple Sclerosis Research Studies (6 papers), Systemic Lupus Erythematosus Research (4 papers), T-cell and B-cell Immunology (3 papers), Bioinformatics and Genomic Networks (1 paper), Digital Imaging for Blood Diseases (1 paper), Computational Drug Discovery Methods (1 paper), Rheumatoid Arthritis Research and Therapies (1 paper) and Fungal Infections and Studies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (145 citations), Pathology and Forensic Medicine (123 citations), Health Informatics (6 citations), Molecular Biology (269 citations) and Immunology (67 citations). Antoine Lizée has collaborated with scholars based in United States, France and Australia. Frequent co-authors include Pouya Khankhanian, Sergio E. Baranzini, Daniel Himmelstein, Sabrina Chen, Dexter Hadley, Leo Brueggeman, Ari Green, Christine Hessler, Pierre‐Antoine Gourraud and Bruce Cree. Their work appears in journals such as The Pharmacogenomics Journal, Neurology, eLife, Journal of Medical Internet Research and Journal of Neurology.
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.