Antanas Vaitkus
- Materials Chemistry top 10%
- Molecular Biology
- Electrical and Electronic Engineering
- Mechanical Engineering
- Electronic, Optical and Magnetic Materials
- Co-authors
- S. GražulisAndrius MerkysM. QuirósFei LongGarib N. MurshudovPaul EmsleyRobert A. NichollsVisvaldas Kairys
- Topics
- Computational Drug Discovery Methods (7 papers)Machine Learning in Materials Science (4 papers)Crystallography and molecular interactions (4 papers)
- Journals
- Journal of Applied CrystallographyJournal of CheminformaticsActa Crystallographica Section D Structural Biology
- Partner nations
- LithuaniaSpainUnited Kingdom
In The Last Decade
Antanas Vaitkus
13 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Materials Chemistry 568
- Molecular Biology 249
- Electrical and Electronic Engineering 187
- Mechanical Engineering 118
- Electronic, Optical and Magnetic Materials 108
Countries citing papers authored by Antanas Vaitkus
This map shows the geographic impact of Antanas Vaitkus'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 Antanas Vaitkus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Antanas Vaitkus more than expected).
Fields of papers citing papers by Antanas Vaitkus
This network shows the impact of papers produced by Antanas Vaitkus. 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 Antanas Vaitkus. The network helps show where Antanas Vaitkus may publish in the future.
Co-authorship network of co-authors of Antanas Vaitkus
This figure shows the co-authorship network connecting the top 25 collaborators of Antanas Vaitkus. A scholar is included among the top collaborators of Antanas Vaitkus 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 Antanas Vaitkus. Antanas Vaitkus is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 53 | |
| 2 | 57 | |
| 3 | 1 | |
| 4 | Validation of the Crystallography Open Database using the Crystallographic Information Frameworkbreakdown → | 252 |
| 5 | 1 | |
| 6 | 38 | |
| 7 | 175 | |
| 8 | 1 | |
| 9 | AceDRG: a stereochemical description generator for ligandsbreakdown → | 261 |
| 10 | 15 | |
| 11 | 150 | |
| 12 | 155 | |
| 13 | 2 |
About Antanas Vaitkus
Antanas Vaitkus is a scholar working on Physical and Theoretical Chemistry, Computational Theory and Mathematics and Information Systems and Management, having authored 13 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Machine Learning in Materials Science (4 papers) and Crystallography and molecular interactions (4 papers). The work is most often cited by research in Materials Chemistry (568 citations), Structural Biology (10 citations) and Inorganic Chemistry (82 citations). Antanas Vaitkus has collaborated with scholars based in Lithuania, Spain and United Kingdom. Frequent co-authors include S. Gražulis, Andrius Merkys, M. Quirós, Fei Long, Garib N. Murshudov, Paul Emsley, Robert A. Nicholls, Visvaldas Kairys, Thomas Sander and Paul Thiessen. Their work appears in journals such as Journal of Applied Crystallography, Journal of Cheminformatics and Acta Crystallographica Section D Structural Biology.
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.