Gene E. Ananiev
Impact in
- Developmental Neuroscience top 10%
- Neurogenesis and neuroplasticity mechanisms
-
- Pluripotent Stem Cells Research
- CRISPR and Genetic Engineering
Papers in
-
- CRISPR and Genetic Engineering 3
- Epigenetics and DNA Methylation 2
- Genetics 6
- Genetics and Neurodevelopmental Disorders 4
- Bacterial Genetics and Biotechnology 2
- 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)Yan Liu (1 shared paper)Xiaofen Zhong (1 shared paper)
- Journals
- Marine Drugs (2 papers)PLoS ONE (2 papers)Journal of Chemical Information and Modeling (2 papers)Stem Cells (1 paper)SLAS DISCOVERY (1 paper)
- Partner nations
- United StatesRussiaSaudi Arabia
In The Last Decade
Gene E. Ananiev
20 papers receiving 754 citations
Peers
Comparison fields: 5 of 87
- Developmental Neuroscience 58
- Molecular Biology 523
- Genetics 204
- Cognitive Neuroscience 116
- Molecular Medicine 29
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
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 162 | |
| 2 | 2014 | 157 | |
| 3 | 2017 | 115 | |
| 4 | 2007 | 108 | |
| 5 | 2018 | 48 | |
| 6 | 2016 | 46 | |
| 7 | 2008 | 31 | |
| 8 | 2017 | 22 | |
| 9 | 2014 | 13 | |
| 10 | 2018 | 13 | |
| 11 | 2022 | 12 | |
| 12 | 2024 | 9 | |
| 13 | 2022 | 8 | |
| 14 | 2019 | 7 | |
| 15 | 2023 | 7 | |
| 16 | 2021 | 4 | |
| 17 | 2025 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2023 | 1 |
About Gene E. Ananiev
Gene E. Ananiev is a scholar working on Molecular Biology, Genetics, Pharmacology, Computational Theory and Mathematics and Materials Chemistry, having authored 20 papers that have together received 766 indexed citations. Recurring topics across this work include Microbial Natural Products and Biosynthesis (4 papers), Genetics and Neurodevelopmental Disorders (4 papers), Computational Drug Discovery Methods (3 papers), Machine Learning in Materials Science (3 papers), CRISPR and Genetic Engineering (3 papers), Bacterial Genetics and Biotechnology (2 papers), Autism Spectrum Disorder Research (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Developmental Neuroscience (58 citations), Molecular Biology (523 citations), Genetics (204 citations), Cognitive Neuroscience (116 citations) and Molecular Medicine (29 citations). Gene E. Ananiev has collaborated with scholars based in United States, Russia and Saudi Arabia. Frequent co-authors include Qiang Chang, Hongda Li, David C. Schwartz, Jill Herschleb, F. Michael Hoffmann, Scott A. Wildman, Yan Liu, Xiaofen Zhong, James L. Keck and Mitra Farnoodian. Their work appears in journals such as Marine Drugs, PLoS ONE, Journal of Chemical Information and Modeling, Stem Cells and SLAS DISCOVERY.
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.