Eugene Davydov

10.5k total citations · 4 hit papers
9 papers, 3.2k citations indexed

About

Eugene Davydov is a scholar working on Molecular Biology, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Eugene Davydov has authored 9 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Information Systems and 2 papers in Computer Networks and Communications. Recurrent topics in Eugene Davydov's work include RNA and protein synthesis mechanisms (3 papers), Genomics and Phylogenetic Studies (3 papers) and Genetic Associations and Epidemiology (2 papers). Eugene Davydov is often cited by papers focused on RNA and protein synthesis mechanisms (3 papers), Genomics and Phylogenetic Studies (3 papers) and Genetic Associations and Epidemiology (2 papers). Eugene Davydov collaborates with scholars based in United States and Russia. Eugene Davydov's co-authors include Serafim Batzoglou, Gregory M. Cooper, Arend Sidow, Marina Sirota, David L. Goode, Eric D. Green, Michael Brudno, NISC Comparative Sequencing Program, Todd Phillips and Daniel Golovin and has published in prestigious journals such as PLoS ONE, Genome Research and PLoS Computational Biology.

In The Last Decade

Eugene Davydov

9 papers receiving 3.1k citations

Hit Papers

Identifying a High Fraction of the Human Genome to be und... 2003 2026 2010 2018 2010 2003 2013 2015 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Eugene Davydov United States 7 1.5k 995 601 420 358 9 3.2k
Tijl De Bie Belgium 25 1.6k 1.1× 541 0.5× 691 1.1× 294 0.7× 618 1.7× 124 3.6k
Mark D. Wilkinson Spain 28 1.3k 0.9× 231 0.2× 483 0.8× 652 1.6× 534 1.5× 111 3.2k
Esko Ukkonen Finland 30 3.8k 2.5× 532 0.5× 2.2k 3.7× 449 1.1× 378 1.1× 117 6.0k
Yarden Katz United States 19 1.3k 0.9× 167 0.2× 1.3k 2.1× 732 1.7× 96 0.3× 24 2.9k
Kevin Y. Yip Hong Kong 33 2.2k 1.5× 433 0.4× 521 0.9× 297 0.7× 191 0.5× 106 3.4k
Kaizhong Zhang Canada 35 2.2k 1.4× 355 0.4× 1.5k 2.5× 756 1.8× 145 0.4× 126 5.4k
Thomas L. Casavant United States 35 2.4k 1.6× 1.1k 1.1× 223 0.4× 409 1.0× 117 0.3× 134 5.3k
Alan Colman Australia 55 7.4k 4.9× 3.3k 3.3× 542 0.9× 821 2.0× 417 1.2× 235 11.0k
Ming Hao United States 26 2.4k 1.6× 434 0.4× 452 0.8× 130 0.3× 243 0.7× 126 5.1k
Shaoliang Peng China 28 1.5k 1.0× 121 0.1× 441 0.7× 286 0.7× 168 0.5× 190 3.1k

Countries citing papers authored by Eugene Davydov

Since Specialization
Citations

This map shows the geographic impact of Eugene Davydov'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 Eugene Davydov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eugene Davydov more than expected).

Fields of papers citing papers by Eugene Davydov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eugene Davydov. 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 Eugene Davydov. The network helps show where Eugene Davydov may publish in the future.

Co-authorship network of co-authors of Eugene Davydov

This figure shows the co-authorship network connecting the top 25 collaborators of Eugene Davydov. A scholar is included among the top collaborators of Eugene Davydov 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 Eugene Davydov. Eugene Davydov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Sculley, D., Gary D. Holt, Daniel Golovin, et al.. (2015). Hidden technical debt in Machine learning systems. Neural Information Processing Systems. 28. 2503–2511. 450 indexed citations breakdown →
2.
Sculley, D., Gary D. Holt, Daniel Golovin, et al.. (2014). Machine Learning: The High Interest Credit Card of Technical Debt. 125 indexed citations
3.
McMahan, H. Brendan, Gary D. Holt, D. Sculley, et al.. (2013). Ad click prediction. 1222–1230. 509 indexed citations breakdown →
4.
Davydov, Eugene, David L. Goode, Marina Sirota, et al.. (2010). Identifying a High Fraction of the Human Genome to be under Selective Constraint Using GERP++. PLoS Computational Biology. 6(12). e1001025–e1001025. 1068 indexed citations breakdown →
5.
Goode, David L., Gregory M. Cooper, Jeremy Schmutz, et al.. (2010). Evolutionary constraint facilitates interpretation of genetic variation in resequenced human genomes. Genome Research. 20(3). 301–310. 55 indexed citations
6.
Chen, Rong, Eugene Davydov, Marina Sirota, & Atul J. Butte. (2010). Non-Synonymous and Synonymous Coding SNPs Show Similar Likelihood and Effect Size of Human Disease Association. PLoS ONE. 5(10). e13574–e13574. 150 indexed citations
7.
Davydov, Eugene & Serafim Batzoglou. (2006). A computational model for RNA multiple structural alignment. Theoretical Computer Science. 368(3). 205–216. 5 indexed citations
8.
Brudno, Michael, Gregory M. Cooper, Eugene Davydov, et al.. (2003). LAGAN and Multi-LAGAN: Efficient Tools for Large-Scale Multiple Alignment of Genomic DNA. Genome Research. 13(4). 721–731. 876 indexed citations breakdown →
9.
Lubashevsky, Ihor, et al.. (2002). <title>Nondiffusive heat propagation in tissue under local strong heating</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 4617. 236–244. 1 indexed citations

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.

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