Dmitry Korkin

3.2k total citations
71 papers, 1.9k citations indexed

About

Dmitry Korkin is a scholar working on Molecular Biology, Computational Theory and Mathematics and Genetics. According to data from OpenAlex, Dmitry Korkin has authored 71 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Molecular Biology, 11 papers in Computational Theory and Mathematics and 11 papers in Genetics. Recurrent topics in Dmitry Korkin's work include Protein Structure and Dynamics (21 papers), Bioinformatics and Genomic Networks (19 papers) and Genomics and Phylogenetic Studies (13 papers). Dmitry Korkin is often cited by papers focused on Protein Structure and Dynamics (21 papers), Bioinformatics and Genomic Networks (19 papers) and Genomics and Phylogenetic Studies (13 papers). Dmitry Korkin collaborates with scholars based in United States, Canada and United Kingdom. Dmitry Korkin's co-authors include Andrej Săli, Frank Alber, Maya Topf, Chi‐Ren Shyu, Nan Zhao, Melissa G. Mitchum, Fred P. Davis, Thomas J. Baum, Friedrich Förster and Hongzhu Cui and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Dmitry Korkin

66 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dmitry Korkin United States 22 1.1k 552 219 162 161 71 1.9k
Kengo Sato Japan 22 2.2k 2.0× 346 0.6× 113 0.5× 150 0.9× 82 0.5× 64 2.7k
Takashi Ishida Japan 17 1.7k 1.6× 173 0.3× 337 1.5× 182 1.1× 73 0.5× 70 2.2k
Jean-François Taly Spain 10 904 0.8× 213 0.4× 132 0.6× 37 0.2× 89 0.6× 12 1.4k
Mike Tyka United States 5 903 0.8× 99 0.2× 170 0.8× 122 0.8× 86 0.5× 5 1.8k
Drena Dobbs United States 34 4.2k 4.0× 736 1.3× 190 0.9× 300 1.9× 218 1.4× 83 4.9k
Christophe Blanchet France 18 1.9k 1.8× 348 0.6× 196 0.9× 36 0.2× 156 1.0× 36 2.9k
Jean-François Gibrat France 13 1.9k 1.8× 121 0.2× 391 1.8× 144 0.9× 98 0.6× 34 2.4k
Jaap Heringa Netherlands 33 2.9k 2.7× 226 0.4× 417 1.9× 207 1.3× 281 1.7× 103 3.7k
Daniel Buchan United Kingdom 16 2.8k 2.6× 282 0.5× 424 1.9× 178 1.1× 228 1.4× 24 3.5k
Toshiaki Katayama Japan 17 1.6k 1.5× 127 0.2× 79 0.4× 167 1.0× 52 0.3× 46 2.1k

Countries citing papers authored by Dmitry Korkin

Since Specialization
Citations

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

Fields of papers citing papers by Dmitry Korkin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dmitry Korkin

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

All Works

20 of 20 papers shown
1.
Lu, Senbao, Ziyang Gao, Ben T. Jordan, et al.. (2025). Biosurfer for systematic tracking of regulatory mechanisms leading to protein isoform diversity. Genome Research. 35(4). 1012–1024.
2.
Prjibelski, Andrey D., Wen Hu, Lieke Michielsen, et al.. (2025). A spatial long-read approach at near-single-cell resolution reveals developmental regulation of splicing and polyadenylation sites in distinct cortical layers and cell types. Nature Communications. 16(1). 8093–8093. 1 indexed citations
3.
Sun, Huaming, et al.. (2024). Diverse intrinsic properties shape transcript stability and stabilization in Mycolicibacterium smegmatis. NAR Genomics and Bioinformatics. 6(4). lqae147–lqae147. 1 indexed citations
4.
Cui, Hongzhu, Suhas Srinivasan, Ziyang Gao, & Dmitry Korkin. (2023). The Extent of Edgetic Perturbations in the Human Interactome Caused by Population-Specific Mutations. Biomolecules. 14(1). 40–40.
5.
Korkin, Dmitry, et al.. (2023). Asymmetric trichotomous partitioning overcomes dataset limitations in building machine learning models for predicting siRNA efficacy. Molecular Therapy — Nucleic Acids. 33. 93–109. 9 indexed citations
6.
Kitsak, Maksim, Alexander A. Ganin, Ahmed Elmokashfi, et al.. (2023). Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping. Nature Communications. 14(1). 8 indexed citations
7.
Narykov, Oleksandr, Nathan Johnson, & Dmitry Korkin. (2021). Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning. Cell Reports. 37(8). 110045–110045. 6 indexed citations
8.
Wang, Jianying, Thomas J. Baum, R. S. Hussey, et al.. (2020). Phytonematode peptide effectors exploit a host post‐translational trafficking mechanism to the ER using a novel translocation signal. New Phytologist. 229(1). 563–574. 26 indexed citations
9.
Srinivasan, Suhas, et al.. (2020). A hybrid deep clustering approach for robust cell type profiling using single-cell RNA-seq data. RNA. 26(10). 1303–1319. 15 indexed citations
10.
Narykov, Oleksandr, et al.. (2019). DISPOT: a simple knowledge-based protein domain interaction statistical potential. Bioinformatics. 35(24). 5374–5378. 7 indexed citations
11.
Masonbrink, Rick E., Tom Maier, Usha Muppirala, et al.. (2019). The genome of the soybean cyst nematode (Heterodera glycines) reveals complex patterns of duplications involved in the evolution of parasitism genes. BMC Genomics. 20(1). 119–119. 59 indexed citations
12.
Cui, Hongzhu, Nan Zhao, & Dmitry Korkin. (2018). Multilayer View of Pathogenic SNVs in Human Interactome through In Silico Edgetic Profiling. Journal of Molecular Biology. 430(18). 2974–2992. 7 indexed citations
13.
Zhao, Nan, et al.. (2014). Evidence of Positive Selection in Mitochondrial Complexes I and V of the African Elephant. PLoS ONE. 9(4). e92587–e92587. 32 indexed citations
14.
Chen, Zhenzhou, Shanyan Chen, Dmitry Korkin, et al.. (2014). Histological Quantitation of Brain Injury Using Whole Slide Imaging: A Pilot Validation Study in Mice. PLoS ONE. 9(3). e92133–e92133. 23 indexed citations
15.
Wan, Xiu‐Feng, et al.. (2013). Extreme Evolutionary Conservation of Functionally Important Regions in H1N1 Influenza Proteome. PLoS ONE. 8(11). e81027–e81027. 10 indexed citations
16.
Pang, Bin, Nan Zhao, Michela Becchi, Dmitry Korkin, & Chi‐Ren Shyu. (2012). Accelerating large-scale protein structure alignments with graphics processing units. BMC Research Notes. 5(1). 116–116. 22 indexed citations
17.
Pang, Bin, Xiangyu Kuang, Nan Zhao, Dmitry Korkin, & Chi‐Ren Shyu. (2012). PBSword: a web server for searching similar protein-protein binding sites. Nucleic Acids Research. 40(W1). W428–W434. 3 indexed citations
18.
Zhao, Nan, Bin Pang, Chi‐Ren Shyu, & Dmitry Korkin. (2011). Feature‐based classification of native and non‐native protein–protein interactions: Comparing supervised and semi‐supervised learning approaches. PROTEOMICS. 11(22). 4321–4330. 10 indexed citations
19.
Wang, Qingguo, Dmitry Korkin, & Yi Shang. (2009). Efficient dominant point algorithms for the multiple longest common subsequence (MLCS) problem. International Joint Conference on Artificial Intelligence. 1494–1499. 9 indexed citations
20.
Korkin, Dmitry, Fred P. Davis, & Andrej Săli. (2005). Localization of protein‐binding sites within families of proteins. Protein Science. 14(9). 2350–2360. 35 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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