Quentin Haas

461 total citations
10 papers, 301 citations indexed

About

Quentin Haas is a scholar working on Molecular Biology, Immunology and Artificial Intelligence. According to data from OpenAlex, Quentin Haas has authored 10 papers receiving a total of 301 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Immunology and 2 papers in Artificial Intelligence. Recurrent topics in Quentin Haas's work include Glycosylation and Glycoproteins Research (3 papers), Meta-analysis and systematic reviews (2 papers) and Immunotherapy and Immune Responses (2 papers). Quentin Haas is often cited by papers focused on Glycosylation and Glycoproteins Research (3 papers), Meta-analysis and systematic reviews (2 papers) and Immunotherapy and Immune Responses (2 papers). Quentin Haas collaborates with scholars based in Switzerland, Netherlands and Germany. Quentin Haas's co-authors include Stephan von Gunten, Cédric Simillion, Douglas Teodoro, Hans‐Uwe Simon, Gabriela M. Baerlocher, Nikolay Borissov, Monika Haubitz, Beatrice Minder, Doris Kopp‐Heim and Poorya Amini and has published in prestigious journals such as Frontiers in Immunology, PLoS Pathogens and Journal of the American Medical Informatics Association.

In The Last Decade

Quentin Haas

9 papers receiving 297 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Quentin Haas Switzerland 6 187 161 55 26 24 10 301
María José Ferri Spain 8 158 0.8× 101 0.6× 89 1.6× 24 0.9× 22 0.9× 11 330
Angela Hu United States 11 258 1.4× 79 0.5× 139 2.5× 22 0.8× 46 1.9× 23 470
Nuala Moran United Kingdom 11 124 0.7× 38 0.2× 45 0.8× 26 1.0× 26 1.1× 50 347
Kamran Kafi United States 11 96 0.5× 104 0.6× 130 2.4× 109 4.2× 17 0.7× 17 342
Anca Chelariu-Raicu Germany 12 179 1.0× 92 0.6× 142 2.6× 20 0.8× 12 0.5× 42 434
Soo Young Hwang United States 9 101 0.5× 63 0.4× 52 0.9× 24 0.9× 18 0.8× 31 298
Audra N. Iness United States 11 230 1.2× 56 0.3× 85 1.5× 12 0.5× 4 0.2× 17 413
Janet C. Reid Australia 9 189 1.0× 34 0.2× 62 1.1× 7 0.3× 19 0.8× 16 327
V. Nüßler Germany 10 146 0.8× 51 0.3× 119 2.2× 10 0.4× 4 0.2× 23 336
Yan Leyfman United States 9 117 0.6× 71 0.4× 195 3.5× 7 0.3× 7 0.3× 25 338

Countries citing papers authored by Quentin Haas

Since Specialization
Citations

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

Fields of papers citing papers by Quentin Haas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Quentin Haas

This figure shows the co-authorship network connecting the top 25 collaborators of Quentin Haas. A scholar is included among the top collaborators of Quentin Haas 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 Quentin Haas. Quentin Haas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
1.
Meer, F J van der, et al.. (2024). Analysis of eligibility criteria clusters based on large language models for clinical trial design. Journal of the American Medical Informatics Association. 32(3). 447–458.
2.
Haas, Quentin, Nikolay Borissov, Michel Jacques Counotte, et al.. (2023). Ensemble of deep learning language models to support the creation of living systematic reviews for the COVID-19 literature. Systematic Reviews. 12(1). 94–94. 5 indexed citations
3.
Haas, Quentin, Andrej Benjak, Monika Haubitz, et al.. (2022). Siglec-7 represents a glyco-immune checkpoint for non-exhausted effector memory CD8+ T cells with high functional and metabolic capacities. Frontiers in Immunology. 13. 996746–996746. 21 indexed citations
4.
Borissov, Nikolay, Quentin Haas, Beatrice Minder, et al.. (2022). Reducing systematic review burden using Deduklick: a novel, automated, reliable, and explainable deduplication algorithm to foster medical research. Systematic Reviews. 11(1). 172–172. 64 indexed citations
5.
Haas, Quentin, et al.. (2021). Vaccine Development in the Time of COVID-19: The Relevance of the Risklick AI to Assist in Risk Assessment and Optimize Performance. Frontiers in Digital Health. 3. 745674–745674. 3 indexed citations
6.
Haas, Quentin, et al.. (2021). The Distinct Roles of Sialyltransferases in Cancer Biology and Onco-Immunology. Frontiers in Immunology. 12. 799861–799861. 73 indexed citations
7.
Démoulins, Thomas, G. Tuba Barut, Béatrice Zumkehr, et al.. (2021). Pulmonary mesenchymal stem cells are engaged in distinct steps of host response to respiratory syncytial virus infection. PLoS Pathogens. 17(7). e1009789–e1009789. 5 indexed citations
8.
9.
Haas, Quentin, Kayluz Frias Boligan, Camilla Jandus, et al.. (2019). Siglec-9 Regulates an Effector Memory CD8+ T-cell Subset That Congregates in the Melanoma Tumor Microenvironment. Cancer Immunology Research. 7(5). 707–718. 110 indexed citations
10.
Haas, Quentin, Cédric Simillion, & Stephan von Gunten. (2018). A Cartography of Siglecs and Sialyltransferases in Gynecologic Malignancies: Is There a Road Towards a Sweet Future?. Frontiers in Oncology. 8. 68–68. 12 indexed citations

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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2026