Oliver Wieder

751 total citations · 1 hit paper
9 papers, 462 citations indexed

About

Oliver Wieder is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Oliver Wieder has authored 9 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computational Theory and Mathematics, 6 papers in Molecular Biology and 5 papers in Materials Chemistry. Recurrent topics in Oliver Wieder's work include Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (5 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Oliver Wieder is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (5 papers) and Metabolomics and Mass Spectrometry Studies (2 papers). Oliver Wieder collaborates with scholars based in Austria, France and Italy. Oliver Wieder's co-authors include Thierry Langer, Thomas Seidel, Arthur Garon, Mélaine A. Kuenemann, Stefan M. Kohlbacher, Marcus Wieder, Ernst Urban, Sharon D. Bryant, Christophe Meyer and Angelica Mazzolari and has published in prestigious journals such as Molecules, Journal of Chemical Information and Modeling and Frontiers in Chemistry.

In The Last Decade

Oliver Wieder

9 papers receiving 452 citations

Hit Papers

A compact review of molecular property prediction with gr... 2020 2026 2022 2024 2020 100 200 300

Peers

Oliver Wieder
Comparison fields: 5 of 88
  • Computational Theory and Mathematics 311
  • Materials Chemistry 230
  • Molecular Biology 190
  • Artificial Intelligence 67
  • Organic Chemistry 40
Replace Stefan M. Kohlbacher with:
Stefan M. Kohlbacher Austria
Arthur Garon Austria
Pavel Karpov Russia
Sabrina Jaeger-Honz Germany
Pavel Sidorov France
Ben Liao China
Sergey Sosnin Russia
Jaechang Lim South Korea
Kuzma Khrabrov United States
Simon Johansson Sweden
Stefan M. Kohlbacher Austria View profile →
Citations per field, relative to Oliver Wieder
Oliver Wieder · 1×
Citations per year, relative to Oliver Wieder
Oliver Wieder · 1×

Countries citing papers authored by Oliver Wieder

Since Specialization
Citations

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

Fields of papers citing papers by Oliver Wieder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oliver Wieder

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

All Works

9 of 9 papers shown
# Work Indexed citations
1 1
2 2
3 13
4 23
5 23
6
A compact review of molecular property prediction with graph neural networks breakdown →
318
7 24
8 2
9 56

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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