G.I. Bachmanova
- Pharmacology top 2%
- Molecular Biology
- Oncology
- Computational Theory and Mathematics top 10%
- Spectroscopy
- Co-authors
- Jeremy J. RamsdenAlexander I. ArchakovIrina P. KanaevaA.I. ArchakovDaiva BironaitėKarin ÖllingerYakov M. KoenГ.П. Кузнецова
- Topics
- Pharmacogenetics and Drug Metabolism (10 papers)Drug Transport and Resistance Mechanisms (6 papers)Computational Drug Discovery Methods (6 papers)
- Partner nations
- RussiaUnited KingdomJapan
In The Last Decade
G.I. Bachmanova
22 papers receiving 361 citations
Peers
Comparison fields: 5 of 72
- Pharmacology 174
- Molecular Biology 173
- Oncology 90
- Computational Theory and Mathematics 64
- Spectroscopy 54
Countries citing papers authored by G.I. Bachmanova
This map shows the geographic impact of G.I. Bachmanova'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 G.I. Bachmanova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites G.I. Bachmanova more than expected).
Fields of papers citing papers by G.I. Bachmanova
This network shows the impact of papers produced by G.I. Bachmanova. 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 G.I. Bachmanova. The network helps show where G.I. Bachmanova may publish in the future.
Co-authorship network of co-authors of G.I. Bachmanova
This figure shows the co-authorship network connecting the top 25 collaborators of G.I. Bachmanova. A scholar is included among the top collaborators of G.I. Bachmanova 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 G.I. Bachmanova. G.I. Bachmanova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 32 | |
| 3 | 27 | |
| 4 | 5 | |
| 5 | 13 | |
| 6 | 62 | |
| 7 | 54 | |
| 8 | 19 | |
| 9 | 44 | |
| 10 | 21 | |
| 11 | 9 | |
| 12 | 23 | |
| 13 | 8 | |
| 14 | 8 | |
| 15 | 4 | |
| 16 | [Influence of heliotrin on the rat liver microsomal oxidation system]. | 2 |
| 17 | 9 | |
| 18 | [Interaction of acrylonitrile with the microsomal oxidation system of the rat liver]. | 1 |
| 19 | 11 | |
| 20 | 16 |
About G.I. Bachmanova
G.I. Bachmanova is a scholar working on Pharmacology, Biochemistry and Computational Theory and Mathematics, having authored 23 papers that have together received 380 indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (10 papers), Drug Transport and Resistance Mechanisms (6 papers) and Computational Drug Discovery Methods (6 papers). The work is most often cited by research in Pharmacology (174 citations), Computational Theory and Mathematics (64 citations) and Toxicology (13 citations). G.I. Bachmanova has collaborated with scholars based in Russia, United Kingdom and Japan. Frequent co-authors include Jeremy J. Ramsden, Alexander I. Archakov, Alexander I. Archakov, Irina P. Kanaeva, A.I. Archakov, Daiva Bironaitė, Karin Öllinger, Yakov M. Koen, Г.П. Кузнецова and Žilvinas Anusevičius. Their work appears in journals such as Biochemistry, Biochemical Journal and Biochemical and Biophysical Research Communications.
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.