Oleksandr Skyba

1.3k total citations
17 papers, 797 citations indexed

About

Oleksandr Skyba is a scholar working on Plant Science, Molecular Biology and Biomedical Engineering. According to data from OpenAlex, Oleksandr Skyba has authored 17 papers receiving a total of 797 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Plant Science, 6 papers in Molecular Biology and 4 papers in Biomedical Engineering. Recurrent topics in Oleksandr Skyba's work include Enzyme-mediated dye degradation (5 papers), Wood Treatment and Properties (3 papers) and Biofuel production and bioconversion (3 papers). Oleksandr Skyba is often cited by papers focused on Enzyme-mediated dye degradation (5 papers), Wood Treatment and Properties (3 papers) and Biofuel production and bioconversion (3 papers). Oleksandr Skyba collaborates with scholars based in Canada, United States and Czechia. Oleksandr Skyba's co-authors include Shawn D. Mansfield, Carl J. Douglas, Dan Cullen, John Ralph, Michael D. Mozuch, Grzegorz Sabat, Robert A. Blanchette, Jill Gaskell, Philip J. Kersten and Igor V. Grigoriev and has published in prestigious journals such as SHILAP Revista de lepidopterología, Applied and Environmental Microbiology and PLANT PHYSIOLOGY.

In The Last Decade

Oleksandr Skyba

15 papers receiving 780 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Oleksandr Skyba Canada 14 470 300 246 136 101 17 797
Faride Unda Canada 20 688 1.5× 433 1.4× 608 2.5× 86 0.6× 49 0.5× 38 1.1k
Guanzheng Qu China 19 683 1.5× 178 0.6× 674 2.7× 41 0.3× 80 0.8× 85 1.1k
Anni Harju Finland 21 308 0.7× 142 0.5× 305 1.2× 61 0.4× 101 1.0× 49 1.1k
Barry Goldfarb United States 25 763 1.6× 103 0.3× 577 2.3× 45 0.3× 168 1.7× 62 1.4k
Frank Bedon Australia 17 620 1.3× 73 0.2× 584 2.4× 77 0.6× 88 0.9× 21 971
Rebecca Van Acker Belgium 15 623 1.3× 575 1.9× 720 2.9× 125 0.9× 31 0.3× 19 1.1k
Peter Immerzeel Sweden 17 910 1.9× 418 1.4× 592 2.4× 182 1.3× 17 0.2× 24 1.4k
Pierre Sivadon France 18 383 0.8× 157 0.5× 755 3.1× 53 0.4× 51 0.5× 20 1.1k
Rebecca A. Smith United States 18 802 1.7× 604 2.0× 842 3.4× 162 1.2× 41 0.4× 31 1.4k
Brigitte Pollet France 8 514 1.1× 376 1.3× 670 2.7× 126 0.9× 31 0.3× 9 916

Countries citing papers authored by Oleksandr Skyba

Since Specialization
Citations

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

Fields of papers citing papers by Oleksandr Skyba

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oleksandr Skyba

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

All Works

17 of 17 papers shown
1.
2.
Skyba, Oleksandr, et al.. (2024). Mathematical models creation for calculating dimensional accuracy at the construction stages of an analytical standard using the chain method. Technology audit and production reserves. 1(1(75)). 26–34.
3.
Champigny, Marc J., Faride Unda, Oleksandr Skyba, et al.. (2019). Learning from methylomes: epigenomic correlates of Populus balsamifera traits based on deep learning models of natural DNA methylation. Plant Biotechnology Journal. 18(6). 1361–1375. 14 indexed citations
4.
McKown, Athena D., Jaroslav Klápště, Robert D. Guy, et al.. (2017). Sexual homomorphism in dioecious trees: extensive tests fail to detect sexual dimorphism in Populus. Scientific Reports. 7(1). 49 indexed citations
5.
Skyba, Oleksandr, Dan Cullen, Carl J. Douglas, & Shawn D. Mansfield. (2016). Gene Expression Patterns of Wood Decay Fungi Postia placenta and Phanerochaete chrysosporium Are Influenced by Wood Substrate Composition during Degradation. Applied and Environmental Microbiology. 82(14). 4387–4400. 33 indexed citations
6.
Whitehill, Justin G. A., Hannah Henderson, Mathias Schuetz, et al.. (2015). Histology and cell wall biochemistry of stone cells in the physical defence of conifers against insects. Plant Cell & Environment. 39(8). 1646–1661. 29 indexed citations
7.
Gaskell, Jill, Michael D. Mozuch, Philip J. Kersten, et al.. (2014). Influence of Populus Genotype on Gene Expression by the Wood Decay Fungus Phanerochaete chrysosporium. Applied and Environmental Microbiology. 80(18). 5828–5835. 25 indexed citations
8.
Porth, Ilga, Jaroslav Klápště, Oleksandr Skyba, et al.. (2013). Network analysis reveals the relationship among wood properties, gene expression levels and genotypes of natural Populus trichocarpa accessions. New Phytologist. 200(3). 727–742. 24 indexed citations
9.
Skyba, Oleksandr, Carl J. Douglas, & Shawn D. Mansfield. (2013). Syringyl-Rich Lignin Renders Poplars More Resistant to Degradation by Wood Decay Fungi. Applied and Environmental Microbiology. 79(8). 2560–2571. 96 indexed citations
10.
Porth, Ilga, Jaroslav Klápště, Oleksandr Skyba, et al.. (2013). Genome‐wide association mapping for wood characteristics in Populus identifies an array of candidate single nucleotide polymorphisms. New Phytologist. 200(3). 710–726. 106 indexed citations
11.
Porth, Ilga, Athena D. McKown, Richard C. Hamelin, et al.. (2013). Extensive Functional Pleiotropy ofREVOLUTASubstantiated through Forward Genetics    . PLANT PHYSIOLOGY. 164(2). 548–554. 14 indexed citations
12.
Porth, Ilga, Jaroslav Klápště, Oleksandr Skyba, et al.. (2012). Populus trichocarpacell wall chemistry and ultrastructure trait variation, genetic control and genetic correlations. New Phytologist. 197(3). 777–790. 76 indexed citations
13.
Wymelenberg, Amber Vanden, Jill Gaskell, Michael D. Mozuch, et al.. (2011). Significant Alteration of Gene Expression in Wood Decay Fungi Postia placenta and Phanerochaete chrysosporium by Plant Species. Applied and Environmental Microbiology. 77(13). 4499–4507. 87 indexed citations
14.
Wymelenberg, Amber Vanden, Jill Gaskell, Michael D. Mozuch, et al.. (2010). Comparative Transcriptome and Secretome Analysis of Wood Decay FungiPostia placentaandPhanerochaete chrysosporium. Applied and Environmental Microbiology. 76(11). 3599–3610. 185 indexed citations
15.
Skyba, Oleksandr, Francis W. M. R. Schwarze, & Peter Niemz. (2009). Physical and mechanical properties of thermo-hygro-mechanically (THM) - densified wood.. DORA Empa (Swiss Federal Laboratories for Materials Science and Technology (Empa)). 54(2). 1–18. 27 indexed citations
16.
Skyba, Oleksandr, Peter Niemz, & Francis W. M. R. Schwarze. (2009). Resistance of thermo-hygro-mechanically (THM) densified wood to degradation by white rot fungi. Holzforschung. 63(5). 639–646. 13 indexed citations
17.
Skyba, Oleksandr, Peter Niemz, & Francis W. M. R. Schwarze. (2008). Degradation of thermo-hygro-mechanically (THM)-densified wood by soft-rot fungi. Holzforschung. 62(3). 277–283. 19 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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