Gene E. Ananiev
Impact in
- Developmental Neuroscience top 10%
- Pharmacology top 5%
- Microbial Natural Products and Biosynthesis
Papers in
-
- Microbial Natural Products and Biosynthesis 6
-
- CRISPR and Genetic Engineering 3
- Pluripotent Stem Cells Research 3
- Co-authors
- Qiang Chang (2 shared papers)Hongda Li (2 shared papers)David C. Schwartz (2 shared papers)Jill Herschleb (1 shared paper)F. Michael Hoffmann (6 shared papers)Scott A. Wildman (6 shared papers)Qiping Dong (1 shared paper)Ahmed Fathi Mohamed (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (2 papers)Marine Drugs (2 papers)PLoS ONE (2 papers)Journal of Natural Products (1 paper)Biochemistry (1 paper)
- Partner nations
- United StatesBrazilRussia
In The Last Decade
Gene E. Ananiev
22 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 104
- Developmental Neuroscience 60
- Pharmacology 182
- Molecular Biology 762
- Genetics 265
- Biotechnology 81
Countries citing papers authored by Gene E. Ananiev
This map shows the geographic impact of Gene E. Ananiev'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 Gene E. Ananiev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gene E. Ananiev more than expected).
Fields of papers citing papers by Gene E. Ananiev
This network shows the impact of papers produced by Gene E. Ananiev. 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 Gene E. Ananiev. The network helps show where Gene E. Ananiev may publish in the future.
Co-authors
The 25 scholars most cited alongside Gene E. Ananiev, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 239 | |
| 2 | 2011 | 172 | |
| 3 | 2014 | 167 | |
| 4 | 2020 | 149 | |
| 5 | 2007 | 123 | |
| 6 | 2017 | 120 | |
| 7 | 2013 | 78 | |
| 8 | 2018 | 54 | |
| 9 | 2016 | 49 | |
| 10 | 2008 | 31 | |
| 11 | 2017 | 25 | |
| 12 | 2024 | 15 | |
| 13 | 2018 | 14 | |
| 14 | 2022 | 13 | |
| 15 | 2014 | 13 | |
| 16 | 2023 | 12 | |
| 17 | 2022 | 9 | |
| 18 | 2019 | 8 | |
| 19 | 2021 | 5 | |
| 20 | 2024 | 3 |
About Gene E. Ananiev
Gene E. Ananiev is a scholar working on Pharmacology, Molecular Biology, Genetics, Biotechnology and Molecular Medicine, having authored 22 papers that have together received 1.3k indexed citations. Recurring topics across this work include Microbial Natural Products and Biosynthesis (6 papers), Genetics and Neurodevelopmental Disorders (4 papers), CRISPR and Genetic Engineering (3 papers), Pluripotent Stem Cells Research (3 papers), Computational Drug Discovery Methods (3 papers), Machine Learning in Materials Science (3 papers), Marine Sponges and Natural Products (3 papers) and Bacterial Genetics and Biotechnology (2 papers). The work is most often cited by research in Developmental Neuroscience (60 citations), Pharmacology (182 citations), Molecular Biology (762 citations), Genetics (265 citations) and Biotechnology (81 citations). Gene E. Ananiev has collaborated with scholars based in United States, Brazil and Russia. Frequent co-authors include Qiang Chang, Hongda Li, David C. Schwartz, Jill Herschleb, F. Michael Hoffmann, Scott A. Wildman, Qiping Dong, Ahmed Fathi Mohamed, James L. Keck and Ronghui Li. Their work appears in journals such as Journal of Chemical Information and Modeling, Marine Drugs, PLoS ONE, Journal of Natural Products and Biochemistry.
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.