Maxim Teslenko
Impact in
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- Plant and animal studies
- Plant Diversity and Evolution
- Paleontology top 0.2%
Papers in
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- VLSI and Analog Circuit Testing 4
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- Formal Methods in Verification 9
- Co-authors
- Fredrik RonquistAaron E. DarlingBret LargetLiang LiuPaul van der MarkSebastian HöhnaMarc A. SuchardDaniel L. Ayres
- Journals
- IEEE Transactions on Computers (1 paper)Systematic Biology (1 paper)IEEE/ACM Transactions on Computational Biology and Bioinformatics (1 paper)Clinical & Experimental Metastasis (1 paper)Physical Review E (1 paper)
- Partner nations
- SwedenGermanyUnited States
In The Last Decade
Maxim Teslenko
14 papers receiving 20.8k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Ecology, Evolution, Behavior and Systematics 6.7k
- Paleontology 1.9k
- Ecology 5.8k
- Ecological Modeling 919
- Insect Science 2.1k
Countries citing papers authored by Maxim Teslenko
This map shows the geographic impact of Maxim Teslenko'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 Maxim Teslenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxim Teslenko more than expected).
Fields of papers citing papers by Maxim Teslenko
This network shows the impact of papers produced by Maxim Teslenko. 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 Maxim Teslenko. The network helps show where Maxim Teslenko may publish in the future.
Co-authors
The 12 scholars most cited alongside Maxim Teslenko, 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 | 2018 | 3 | |
| 2 | MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space Hit paper breakdown → | 2012 | 20931 |
| 3 | Finding Attractors in Synchronous Multiple-Valued Networks Using SAT-based Bounded Model Checking | 2012 | 2 |
| 4 | 2011 | 114 | |
| 5 | 2010 | 5 | |
| 6 | 2008 | 19 | |
| 7 | 2008 | 26 | |
| 8 | 2007 | 0 | |
| 9 | 2007 | 0 | |
| 10 | 2006 | 0 | |
| 11 | Computing attractors in dynamic networks. | 2005 | 2 |
| 12 | 2005 | 14 | |
| 13 | 2005 | 8 | |
| 14 | 2005 | 18 | |
| 15 | 2005 | 4 | |
| 16 | 2005 | 2 | |
| 17 | 2005 | 2 | |
| 18 | 2004 | 0 | |
| 19 | 2004 | 11 |
About Maxim Teslenko
Maxim Teslenko is a scholar working on Hardware and Architecture, Computational Theory and Mathematics, Software, Artificial Intelligence and Paleontology, having authored 19 papers that have together received 21.2k indexed citations. Recurring topics across this work include Formal Methods in Verification (9 papers), Gene Regulatory Network Analysis (7 papers), VLSI and Analog Circuit Testing (4 papers), Coding theory and cryptography (3 papers), VLSI and FPGA Design Techniques (2 papers), Neural Networks and Applications (2 papers), DNA and Biological Computing (2 papers) and Receptor Mechanisms and Signaling (2 papers). The work is most often cited by research in Ecology, Evolution, Behavior and Systematics (6.7k citations), Paleontology (1.9k citations), Ecology (5.8k citations), Ecological Modeling (919 citations) and Insect Science (2.1k citations). Maxim Teslenko has collaborated with scholars based in Sweden, Germany and United States. Frequent co-authors include Fredrik Ronquist, Aaron E. Darling, Bret Larget, Liang Liu, Paul van der Mark, Sebastian Höhna, Marc A. Suchard, Daniel L. Ayres, John P. Huelsenbeck and Elena Dubrova. Their work appears in journals such as IEEE Transactions on Computers, Systematic Biology, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Clinical & Experimental Metastasis and Physical Review E.
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.