Thomas Scior

69 papers receiving 1.7k citations

Peers

Thomas Scior
Comparison fields: 5 of 127
  • Computational Theory and Mathematics 539
  • Pharmacology 221
  • Inorganic Chemistry 187
  • Molecular Biology 895
  • Organic Chemistry 350
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Tuğba Taşkın‐Tok Türkiye
Chengyuan Liang China
Edmund L. Ellsworth United States
Emanuele Carosati Italy
Tanos C. C. França Brazil
Sebastian Salentin Germany
Vinod Kumar India
Eszter Hazai Hungary
Martin Smieško Switzerland
Venkatesan Jayaprakash India
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Citations per field
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Citations per year

Countries citing papers authored by Thomas Scior

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Scior

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012358
2 2009163
3 2002138
4 201697
5 200592
6 200988
7 200182
8 200663
9 200261
10 200658
11 200550
12 200737
13 201326
14 201025
15 200824
16 201923
17 200822
18 201721
19 201521
20 201121

About Thomas Scior

Thomas Scior is a scholar working on Molecular Biology, Computational Theory and Mathematics, Cellular and Molecular Neuroscience, Organic Chemistry and Inorganic Chemistry, having authored 70 papers that have together received 1.8k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (11 papers), Ion channel regulation and function (8 papers), Vanadium and Halogenation Chemistry (6 papers), Cardiac electrophysiology and arrhythmias (5 papers), Neuroscience and Neuropharmacology Research (5 papers), Synthesis and biological activity (5 papers), Influenza Virus Research Studies (4 papers) and Immune Response and Inflammation (4 papers). The work is most often cited by research in Computational Theory and Mathematics (539 citations), Pharmacology (221 citations), Inorganic Chemistry (187 citations), Molecular Biology (895 citations) and Organic Chemistry (350 citations). Thomas Scior has collaborated with scholars based in Mexico, Germany and United States. Frequent co-authors include Philippe M. Bernard, José L. Medina‐Franco, Karina Martínez‐Mayorga, Quoc‐Tuan Do, Stefan Laufer, Andreas Bender, Karina Cuanalo-Contreras, Gary Tresadern, Dimitris K. Agrafiotis and Thierry Langer. Their work appears in journals such as Current Medicinal Chemistry, Molecules, Journal of Molecular Modeling, Computational and Structural Biotechnology Journal and Journal of Chemical Information and Modeling.

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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