Oleg Sysoev

836 total citations
34 papers, 477 citations indexed

About

Oleg Sysoev is a scholar working on Statistics and Probability, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Oleg Sysoev has authored 34 papers receiving a total of 477 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Statistics and Probability, 8 papers in Artificial Intelligence and 7 papers in Molecular Biology. Recurrent topics in Oleg Sysoev's work include Statistical Methods and Inference (8 papers), Advanced Statistical Methods and Models (6 papers) and Single-cell and spatial transcriptomics (5 papers). Oleg Sysoev is often cited by papers focused on Statistical Methods and Inference (8 papers), Advanced Statistical Methods and Models (6 papers) and Single-cell and spatial transcriptomics (5 papers). Oleg Sysoev collaborates with scholars based in Sweden, United States and United Kingdom. Oleg Sysoev's co-authors include Oleg Burdakov, Xinxiu Li, Mikael Benson, Sandra Lilja, Danuta R. Gawel, Huan Zhang, Samuel Schäfer, Margaretha Stenmarker, David Martínez-Enguita and Thomas Gasslander and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Statistics in Medicine.

In The Last Decade

Oleg Sysoev

29 papers receiving 463 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Oleg Sysoev Sweden 9 110 95 72 71 53 34 477
David Martínez-Enguita Sweden 4 90 0.8× 78 0.8× 60 0.8× 29 0.4× 50 0.9× 7 296
Tony Kam‐Thong Switzerland 6 15 0.1× 62 0.7× 173 2.4× 111 1.6× 21 0.4× 10 688
Margaretha Stenmarker Sweden 4 90 0.8× 78 0.8× 58 0.8× 28 0.4× 50 0.9× 7 309
Girmaw Abebe Tadesse United States 9 18 0.2× 57 0.6× 25 0.3× 166 2.3× 65 1.2× 38 564
Han Yuan Singapore 14 12 0.1× 22 0.2× 91 1.3× 206 2.9× 54 1.0× 55 626
Jinwei Liu United States 6 51 0.5× 60 0.6× 21 0.3× 74 1.0× 34 0.6× 12 364
Nicholas Pudjihartono New Zealand 3 6 0.1× 29 0.3× 64 0.9× 108 1.5× 15 0.3× 5 412
Guadalupe Canahuate United States 12 13 0.1× 33 0.3× 25 0.3× 100 1.4× 14 0.3× 47 369
Zhiqiong Wang China 14 13 0.1× 24 0.3× 68 0.9× 35 0.5× 6 0.1× 68 483

Countries citing papers authored by Oleg Sysoev

Since Specialization
Citations

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

Fields of papers citing papers by Oleg Sysoev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oleg Sysoev

This figure shows the co-authorship network connecting the top 25 collaborators of Oleg Sysoev. A scholar is included among the top collaborators of Oleg Sysoev 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 Oleg Sysoev. Oleg Sysoev 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.
Carlhäll, Carl‐Johan, Pontus Henriksson, Stergios Kechagias, et al.. (2025). Clinically available predictors of obstructive sleep apnoea requiring treatment in type 2 diabetes patients in primary care. Scientific Reports. 15(1). 8710–8710.
2.
3.
Aly, Dina Mansour, et al.. (2024). Multiomics biomarkers were not superior to clinical variables for pan-cancer screening. SHILAP Revista de lepidopterología. 4(1). 234–234. 2 indexed citations
4.
Li, Xinxiu, et al.. (2024). An interactive atlas of genomic, proteomic, and metabolomic biomarkers promotes the potential of proteins to predict complex diseases. Scientific Reports. 14(1). 12710–12710. 6 indexed citations
5.
Li, Xinxiu, Joseph Loscalzo, Oleg Sysoev, et al.. (2024). Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality. Journal of Translational Medicine. 22(1). 444–444. 2 indexed citations
6.
Schäfer, Samuel, Oleg Sysoev, Sandra Lilja, et al.. (2024). scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases. Genome Medicine. 16(1). 42–42. 7 indexed citations
7.
Lilja, Sandra, Xinxiu Li, Eun Jung Lee, et al.. (2023). Multi-organ single-cell analysis reveals an on/off switch system with potential for personalized treatment of immunological diseases. Cell Reports Medicine. 4(3). 100956–100956. 12 indexed citations
8.
Pérez, Wilton, Katarina Ekholm Selling, Rodolfo Peña, et al.. (2021). Trends and factors related to adolescent pregnancies: an incidence trend and conditional inference trees analysis of northern Nicaragua demographic surveillance data. BMC Pregnancy and Childbirth. 21(1). 749–749. 2 indexed citations
9.
Gawel, Danuta R., Eva Bojner Horwitz, Oleg Sysoev, et al.. (2021). [Clinical translation of genomic medicine].. PubMed. 118. 20234.
10.
Källestål, Carina, Rodolfo Peña, Wilton Pérez, et al.. (2020). Assessing the Multiple Dimensions of Poverty. Data Mining Approaches to the 2004–14 Health and Demographic Surveillance System in Cuatro Santos, Nicaragua. Frontiers in Public Health. 7. 409–409. 9 indexed citations
11.
Gawel, Danuta R., et al.. (2020). Analysis of expression profiling data suggests explanation for difficulties in finding biomarkers for nasal polyps. Rhinology Journal. 58(4). 360–367. 4 indexed citations
12.
Björnsson, Bergþór, Carl Borrebaeck, Nils Elander, et al.. (2019). Digital twins to personalize medicine. Genome Medicine. 12(1). 258 indexed citations
13.
Källestål, Carina, Rodolfo Peña, Wilton Pérez, et al.. (2019). Predicting poverty. Data mining approaches to the health and demographic surveillance system in Cuatro Santos, Nicaragua. International Journal for Equity in Health. 18(1). 165–165. 2 indexed citations
14.
Sysoev, Oleg, et al.. (2018). Placement of the decoupling capacitors under the BGA component. SHILAP Revista de lepidopterología. 28(4). 35–40.
15.
Sysoev, Oleg, Anders Grimvall, & Oleg Burdakov. (2011). Bootstrap estimation of the variance of the error term in monotonic regression models. Journal of Statistical Computation and Simulation. 83(4). 627–640. 1 indexed citations
16.
Burdakov, Oleg, Anders Grimvall, & Oleg Sysoev. (2009). Generalized PAV algorithm with block refinement for partially ordered monotonic regression. 23–37. 4 indexed citations
17.
Burdakov, Oleg, Anders Grimvall, & Oleg Sysoev. (2006). Data preordering in generalized PAV algorithm for monotonic regression. Journal of Computational Mathematics. 24(6). 771–790. 9 indexed citations
18.
Burdakov, Oleg, et al.. (2006). An O(n2) algorithm for isotonic regression problems. 25–33. 6 indexed citations
19.
Burdakov, Oleg, et al.. (2005). Hasse diagrams and the generalized PAV-algorithm for monotonic regression in several explanatory variables. Computational Statistics & Data Analysis.
20.
Grimvall, Anders, et al.. (2005). Monotonic regression for the detection of temporal trends in environmental quality data. 54(3). 535–550. 5 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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