Alexander Golbraikh
- Computational Theory and Mathematics top 0.02%
- Molecular Biology top 2%
- Organic Chemistry top 0.5%
- Materials Chemistry top 5%
- Spectroscopy top 1%
- Co-authors
- Alexander TropshaMin ShenZhiyan XiaoKuo‐Hsiung LeeYun-De XiaoScott OloffHao ZhuHarold Kohn
- Topics
- Computational Drug Discovery Methods (42 papers)Machine Learning in Materials Science (7 papers)Protein Structure and Dynamics (6 papers)
- Journals
- Environmental Health PerspectivesJournal of Controlled ReleaseJournal of Medicinal Chemistry
- Partner nations
- United StatesLatviaAustria
In The Last Decade
Alexander Golbraikh
42 papers receiving 7.0k citations
Hit Papers
Peers
Comparison fields: 5 of 163
- Computational Theory and Mathematics 4.9k
- Molecular Biology 2.8k
- Organic Chemistry 2.1k
- Materials Chemistry 836
- Spectroscopy 811
Countries citing papers authored by Alexander Golbraikh
This map shows the geographic impact of Alexander Golbraikh'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 Alexander Golbraikh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Golbraikh more than expected).
Fields of papers citing papers by Alexander Golbraikh
This network shows the impact of papers produced by Alexander Golbraikh. 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 Alexander Golbraikh. The network helps show where Alexander Golbraikh may publish in the future.
Co-authorship network of co-authors of Alexander Golbraikh
This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Golbraikh. A scholar is included among the top collaborators of Alexander Golbraikh 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 Alexander Golbraikh. Alexander Golbraikh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 26 | |
| 4 | 95 | |
| 5 | 37 | |
| 6 | 18 | |
| 7 | 75 | |
| 8 | 43 | |
| 9 | 152 | |
| 10 | 28 | |
| 11 | 364 | |
| 12 | 38 | |
| 13 | 2 | |
| 14 | 19 | |
| 15 | Beware of q2!breakdown → | 3235 |
| 16 | 420 | |
| 17 | 95 | |
| 18 | 38 | |
| 19 | 205 | |
| 20 | 39 |
About Alexander Golbraikh
Alexander Golbraikh is a scholar working on Computational Theory and Mathematics, Spectroscopy and Molecular Biology, having authored 47 papers that have together received 7.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (42 papers), Machine Learning in Materials Science (7 papers) and Protein Structure and Dynamics (6 papers). The work is most often cited by research in Computational Theory and Mathematics (4.9k citations), Organic Chemistry (2.1k citations) and Spectroscopy (811 citations). Alexander Golbraikh has collaborated with scholars based in United States, Latvia and Austria. Frequent co-authors include Alexander Tropsha, Min Shen, Zhiyan Xiao, Kuo‐Hsiung Lee, Yun-De Xiao, Scott Oloff, Hao Zhu, Harold Kohn, Eugene Muratov and Shuxing Zhang. Their work appears in journals such as Environmental Health Perspectives, Journal of Controlled Release and Journal of Medicinal Chemistry.
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.