Е. А. Гладырь

589 total citations
59 papers, 356 citations indexed

About

Е. А. Гладырь is a scholar working on Genetics, General Agricultural and Biological Sciences and Animal Science and Zoology. According to data from OpenAlex, Е. А. Гладырь has authored 59 papers receiving a total of 356 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Genetics, 11 papers in General Agricultural and Biological Sciences and 8 papers in Animal Science and Zoology. Recurrent topics in Е. А. Гладырь's work include Genetic and phenotypic traits in livestock (32 papers), Genetic diversity and population structure (13 papers) and Agriculture and Biological Studies (11 papers). Е. А. Гладырь is often cited by papers focused on Genetic and phenotypic traits in livestock (32 papers), Genetic diversity and population structure (13 papers) and Agriculture and Biological Studies (11 papers). Е. А. Гладырь collaborates with scholars based in Russia, Austria and United Kingdom. Е. А. Гладырь's co-authors include N. A. Zinovieva, Г. Брем, А. А. Sermyagin, А. В. Доцев, Olga Kostyunina, В. Р. Харзинова, Т. Е. Денискова, И. М. Охлопков, Cécile Grohs and Doris Seichter and has published in prestigious journals such as Nature Genetics, SHILAP Revista de lepidopterología and Journal of Animal Science.

In The Last Decade

Е. А. Гладырь

53 papers receiving 322 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Е. А. Гладырь Russia 10 256 55 51 49 45 59 356
Т. Е. Денискова Russia 12 430 1.7× 58 1.1× 91 1.8× 52 1.1× 64 1.4× 82 553
Tatyana Kiselyova Finland 9 397 1.6× 67 1.2× 26 0.5× 31 0.6× 26 0.6× 11 443
А. А. Sermyagin Russia 13 336 1.3× 25 0.5× 99 1.9× 57 1.2× 95 2.1× 89 473
Ruslan Popov Russia 11 476 1.9× 41 0.7× 47 0.9× 74 1.5× 55 1.2× 20 545
Mirjana Ćinkulov Finland 7 393 1.5× 76 1.4× 24 0.5× 38 0.8× 25 0.6× 8 434
А. В. Доцев Russia 14 534 2.1× 83 1.5× 123 2.4× 88 1.8× 91 2.0× 101 701
Lisa Praharani Indonesia 9 333 1.3× 41 0.7× 14 0.3× 59 1.2× 30 0.7× 42 473
Christina Ligda Greece 10 290 1.1× 43 0.8× 19 0.4× 58 1.2× 37 0.8× 30 365
Negar Khayatzadeh Austria 11 196 0.8× 24 0.4× 15 0.3× 32 0.7× 18 0.4× 24 270
R. K. Vijh India 14 382 1.5× 72 1.3× 17 0.3× 124 2.5× 36 0.8× 65 487

Countries citing papers authored by Е. А. Гладырь

Since Specialization
Citations

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

Fields of papers citing papers by Е. А. Гладырь

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Е. А. Гладырь. 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 Е. А. Гладырь. The network helps show where Е. А. Гладырь may publish in the future.

Co-authorship network of co-authors of Е. А. Гладырь

This figure shows the co-authorship network connecting the top 25 collaborators of Е. А. Гладырь. A scholar is included among the top collaborators of Е. А. Гладырь 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 Е. А. Гладырь. Е. А. Гладырь 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.
Денискова, Т. Е., А. В. Доцев, Е. А. Гладырь, et al.. (2025). Examination of Runs of Homozygosity Distribution Patterns and Relevant Candidate Genes of Potential Economic Interest in Russian Goat Breeds Using Whole-Genome Sequencing. Genes. 16(6). 631–631. 2 indexed citations
2.
Гладырь, Е. А., et al.. (2024). The analysis of the Russian beef cattle population on polymorphism of CAPN1 gene. Animal Husbandry and Fodder Production. 107(1). 42–50. 1 indexed citations
3.
Денискова, Т. Е., А. В. Доцев, Е. А. Гладырь, et al.. (2024). Genetic Diversity in the Orenburg Goat Breed Revealed by Single-Nucleotide Polymorphism (SNP) Analysis: Initial Steps in Saving a Threatened Population. Genes. 15(11). 1375–1375. 3 indexed citations
4.
Selionova, Marina, et al.. (2024). Aberdeen Angus beef quality and profitability in dependence of the genotypes. SHILAP Revista de lepidopterología. 548. 2017–2017.
5.
Romanov, Michael N, В.И. Фисинин, Е. А. Гладырь, et al.. (2023). Selective footprints and genes relevant to cold adaptation and other phenotypic traits are unscrambled in the genomes of divergently selected chicken breeds. Journal of Animal Science and Biotechnology. 14(1). 35–35. 16 indexed citations
7.
Гладырь, Е. А., et al.. (2020). Screening of haplotype for cholesterol deficiency genetic defect in the Russian Holstein cattle population. Polish Journal of Veterinary Sciences. 23(2). 313–315. 3 indexed citations
8.
Rebouh, Nazih Y., et al.. (2019). Genetic diversity among local chicken breeds Egypt, using microsatellite DNA markers. Eurasian Journal of Biosciences. 13(2). 1149–1154. 1 indexed citations
9.
Rebouh, Nazih Y., et al.. (2019). Genetic characterization of White Fulani cattle in Nigeria: A comparative study. Journal of Advanced Veterinary and Animal Research. 6(4). 474–474. 6 indexed citations
10.
Гладырь, Е. А., et al.. (2018). Genetic diversity and bottleneck analysis of the Red Steppe cattle based on microsatellite markers. SHILAP Revista de lepidopterología. 8(2). 12–17. 6 indexed citations
11.
Shepelyakovskaya, A. O., et al.. (2017). Immunochemical assay with monoclonal antibodies for detection of staphylococcal enterotoxin H. Journal of Food and Drug Analysis. 26(2). 741–750. 13 indexed citations
12.
Sermyagin, А. А., et al.. (2016). GENOME-WIDE ASSOCIATION STUDY FOR MILK PRODUCTION AND REPRODUCTION TRAITS IN RUSSIAN HOLSTEIN CATTLE POPULATION. Sel skokhozyaistvennaya Biologiya. 51(2). 182–193. 5 indexed citations
13.
Денискова, Т. Е., И. М. Охлопков, А. А. Sermyagin, et al.. (2016). Whole genome SNP scanning of snow sheep (Ovis nivicola). Doklady Biochemistry and Biophysics. 469(1). 288–293. 4 indexed citations
14.
Гладырь, Е. А., et al.. (2016). RECENT ACHIEVEMENTS AND CHALLENGES IN FARM ANIMAL BIOTECHNOLOGY (10th Anniversary Scientific Conference with international participation — analytical review). Sel skokhozyaistvennaya Biologiya. 51(2). 264–268. 1 indexed citations
15.
Харзинова, В. Р., А. А. Sermyagin, Е. А. Гладырь, et al.. (2015). A Study of Applicability of SNP Chips Developed for Bovine and Ovine Species to Whole-Genome Analysis of ReindeerRangifer tarandus. Journal of Heredity. 106(6). esv081–esv081. 19 indexed citations
16.
Денискова, Т. Е., А. В. Доцев, Е. А. Гладырь, et al.. (2015). VALIDATION OF THE SNP PANEL FOR PARENTAGE ASSIGNMENT IN LOCAL RUSSIAN SHEEP BREEDS. Sel skokhozyaistvennaya Biologiya. 50(6). 746–755. 1 indexed citations
17.
Zinovieva, N. A., et al.. (2013). Genetic differentiation of the Novosibirsk population of Primorsky honey bee. Russian Agricultural Sciences. 39(4). 346–349. 1 indexed citations
18.
Zinovieva, N. A., et al.. (2011). Allele pool characteristics of Bashkiria population of Simmental cattle using microsatellites. 2 indexed citations
19.
Zinovieva, N. A., et al.. (2011). Microsatellites as a tool for evaluation of allele pool dynamics when creation of Prioksky type of Middle Russian honey bee. 2 indexed citations
20.
Гладырь, Е. А., et al.. (2011). The characteristics of allele pool of Yakut cattle using microsatellites. 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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