Timur Gimadiev

859 citations
31 papers · 561 indexed · h-index 15
Topics
Computational Drug Discovery Methods (21 papers)Machine Learning in Materials Science (17 papers)Metal complexes synthesis and properties (5 papers)
Partner nations
RussiaFranceJapan

In The Last Decade

Timur Gimadiev

28 papers receiving 560 citations

Peers

Timur Gimadiev
Comparison fields: 5 of 74
  • Computational Theory and Mathematics 319
  • Materials Chemistry 318
  • Molecular Biology 163
  • Organic Chemistry 145
  • Inorganic Chemistry 91
Replace Nosheen A. Gothard with:
Nosheen A. Gothard United States
Ariel Adamski Poland
Rahul Kar India
Olga Klimchuk France
Chris M. Gothard United States
A. Varnek France
Sarah L. J. Trice United States
K.E. Gubina Ukraine
Gregory J. Kirkovits United States
Timur Gimadiev relative to Nosheen A. Gothard United States Nosheen A. Gothard's profile →
Citations per field
00.5×6.3×
Nosheen A. Gothard · 1×
Citations per year

Countries citing papers authored by Timur Gimadiev

Since Specialization
Citations

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

Fields of papers citing papers by Timur Gimadiev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Timur Gimadiev

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 0
4 36
5 8
6 10
7 7
8 14
9 55
10 34
11 49
12 6
13 5
14 28
15 26
16 7
17 19
18 22
19 27
20 8

About Timur Gimadiev

Timur Gimadiev is a scholar working on Computational Theory and Mathematics, Inorganic Chemistry and Materials Chemistry, having authored 31 papers that have together received 561 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (21 papers), Machine Learning in Materials Science (17 papers) and Metal complexes synthesis and properties (5 papers). The work is most often cited by research in Computational Theory and Mathematics (319 citations), Materials Chemistry (318 citations) and Inorganic Chemistry (91 citations). Timur Gimadiev has collaborated with scholars based in Russia, France and Japan. Frequent co-authors include Alexandre Varnek, Timur Madzhidov, Ramil Nugmanov, Igor I. Baskin, Pavel Sidorov, Damir A. Safin, Maria G. Babashkina, И. С. Антипин, Gilles Marcou and F.D. Sokolov. Their work appears in journals such as Angewandte Chemie International Edition, Scientific Reports and International Journal of Molecular Sciences.

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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