Arne Schneuing

719 total citations · 3 hit papers
4 papers, 195 citations indexed

About

Arne Schneuing is a scholar working on Molecular Biology, Computational Theory and Mathematics and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Arne Schneuing has authored 4 papers receiving a total of 195 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Computational Theory and Mathematics and 2 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Arne Schneuing's work include Computational Drug Discovery Methods (4 papers), Protein Structure and Dynamics (3 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). Arne Schneuing is often cited by papers focused on Computational Drug Discovery Methods (4 papers), Protein Structure and Dynamics (3 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). Arne Schneuing collaborates with scholars based in United Kingdom, Switzerland and United States. Arne Schneuing's co-authors include Michael M. Bronstein, Bruno E. Correia, Ilia Igashov, Max Welling, Hamed Khakzad, Casper A. Goverde, Pascal Frossard, H. Stärk, Clément Vignac and Victor García Satorras and has published in prestigious journals such as Nature, Nature Machine Intelligence and Cell Systems.

In The Last Decade

Arne Schneuing

4 papers receiving 188 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Equivariant 3D-conditional diffusion model for molecular linker design

2024 70 citations Ilia Igashov, H. Stärk et al. Nature Machine Intelligence profile →
Structure-based drug design with equivariant diffusion models

2024 52 citations Arne Schneuing, Charles B. Harris et al. Nature Computational Science profile →
Targeting protein–ligand neosurfaces with a generalizable deep learning tool

2025 19 citations Stephen Buckley, Arne Schneuing et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Arne Schneuing United Kingdom	4	119	75	49	24	12	4	195
Ilia Igashov United Kingdom	4	128 1.1×	80 1.1×	60 1.2×	22 0.9×	8 0.7×	5	202
Keisuke Yanagisawa Japan	11	176 1.5×	71 0.9×	20 0.4×	10 0.4×	19 1.6×	20	219
Derek van Tilborg Netherlands	6	145 1.2×	158 2.1×	115 2.3×	20 0.8×	13 1.1×	7	288
Jintu Zhang China	9	181 1.5×	160 2.1×	77 1.6×	10 0.4×	16 1.3×	15	271
Kazuyoshi Ikeda Japan	10	175 1.5×	75 1.0×	30 0.6×	8 0.3×	18 1.5×	28	226
Doris A. Schuetz Austria	6	152 1.3×	113 1.5×	24 0.5×	19 0.8×	24 2.0×	9	198
Nicolas Panel France	9	140 1.2×	46 0.6×	30 0.6×	18 0.8×	13 1.1×	12	170
Bogdan Zagribelnyy Russia	4	124 1.0×	111 1.5×	44 0.9×	12 0.5×	38 3.2×	8	233
Alexander L. Button Switzerland	6	140 1.2×	131 1.7×	89 1.8×	17 0.7×	13 1.1×	7	250
Alejandro Varela‐Rial Spain	6	114 1.0×	109 1.5×	76 1.6×	6 0.3×	14 1.2×	8	183

Countries citing papers authored by Arne Schneuing

Since Specialization

Citations

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

Fields of papers citing papers by Arne Schneuing

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arne Schneuing

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

All Works

Sort: Min cites: Since: Top N: Style:

4 of 4 papers shown

1.

Buckley, Stephen, Arne Schneuing, Martin Pačesa, et al.. (2025). Targeting protein–ligand neosurfaces with a generalizable deep learning tool. Nature. 639(8054). 522–531. 19 indexed citations breakdown →

2.

Igashov, Ilia, H. Stärk, Clément Vignac, et al.. (2024). Equivariant 3D-conditional diffusion model for molecular linker design. Nature Machine Intelligence. 6(4). 417–427. 70 indexed citations breakdown →

3.

Schneuing, Arne, Charles B. Harris, Yuanqi Du, et al.. (2024). Structure-based drug design with equivariant diffusion models. Nature Computational Science. 4(12). 899–909. 52 indexed citations breakdown →

4.

Khakzad, Hamed, Ilia Igashov, Arne Schneuing, et al.. (2023). A new age in protein design empowered by deep learning. Cell Systems. 14(11). 925–939. 54 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.

Explore authors with similar magnitude of impact