Э. К. Хуснутдинова

28.1k total citations
386 papers, 3.0k citations indexed

About

Э. К. Хуснутдинова is a scholar working on Molecular Biology, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Э. К. Хуснутдинова has authored 386 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 126 papers in Molecular Biology, 118 papers in Genetics and 36 papers in Cellular and Molecular Neuroscience. Recurrent topics in Э. К. Хуснутдинова's work include Forensic and Genetic Research (52 papers), Yersinia bacterium, plague, ectoparasites research (36 papers) and Genetic diversity and population structure (22 papers). Э. К. Хуснутдинова is often cited by papers focused on Forensic and Genetic Research (52 papers), Yersinia bacterium, plague, ectoparasites research (36 papers) and Genetic diversity and population structure (22 papers). Э. К. Хуснутдинова collaborates with scholars based in Russia, United Kingdom and Estonia. Э. К. Хуснутдинова's co-authors include Marina Bermisheva, Р. Н. Мустафин, Ildus Kutuev, Richard Villems, С.А. Федорова, Р. И. Хусаинова, А. В. Казанцева, Toomas Kivisild, Lilya U. Dzhemileva and I. R. Gilyazova and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Stroke.

In The Last Decade

Э. К. Хуснутдинова

333 papers receiving 2.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Э. К. Хуснутдинова Russia 26 1.4k 1.0k 328 219 204 386 3.0k
Yiping Hou China 33 2.1k 1.5× 2.2k 2.1× 314 1.0× 452 2.1× 313 1.5× 318 4.4k
William C. Speed United States 35 2.2k 1.6× 1.8k 1.8× 123 0.4× 164 0.7× 280 1.4× 68 4.0k
Luba Kalaydjieva Australia 34 1.4k 1.0× 1.5k 1.5× 183 0.6× 90 0.4× 669 3.3× 95 3.5k
Hong Shi China 25 1.3k 0.9× 628 0.6× 335 1.0× 207 0.9× 63 0.3× 86 2.4k
Batsheva Bonné‐Tamir Israel 34 2.2k 1.6× 1.5k 1.4× 422 1.3× 86 0.4× 288 1.4× 73 4.4k
Qing‐Peng Kong China 36 1.6k 1.1× 2.3k 2.2× 548 1.7× 326 1.5× 62 0.3× 111 3.8k
Limborskaia Sa Russia 26 986 0.7× 1.4k 1.3× 215 0.7× 342 1.6× 530 2.6× 279 3.2k
Marian M. de Pancorbo Spain 26 1.2k 0.8× 1.1k 1.1× 275 0.8× 203 0.9× 89 0.4× 209 2.6k
Óscar Lao Netherlands 32 1.8k 1.3× 1.0k 1.0× 428 1.3× 59 0.3× 82 0.4× 66 3.4k
Carolina Bonilla United Kingdom 29 1.9k 1.4× 1.3k 1.3× 70 0.2× 209 1.0× 64 0.3× 74 3.9k

Countries citing papers authored by Э. К. Хуснутдинова

Since Specialization
Citations

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

Fields of papers citing papers by Э. К. Хуснутдинова

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Э. К. Хуснутдинова. 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 Э. К. Хуснутдинова. The network helps show where Э. К. Хуснутдинова may publish in the future.

Co-authorship network of co-authors of Э. К. Хуснутдинова

This figure shows the co-authorship network connecting the top 25 collaborators of Э. К. Хуснутдинова. A scholar is included among the top collaborators of Э. К. Хуснутдинова 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 Э. К. Хуснутдинова. Э. К. Хуснутдинова 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.
Карунас, А. С., et al.. (2024). Evaluation of Polygenic Risk Score for Prediction of Childhood Onset and Severity of Asthma. International Journal of Molecular Sciences. 26(1). 103–103.
2.
Мустафин, Р. Н. & Э. К. Хуснутдинова. (2024). Involvement of transposable elements in Alzheimer’s disease pathogenesis. Vavilov Journal of Genetics and Breeding. 28(2). 228–238. 3 indexed citations
3.
Хуснутдинова, Э. К., et al.. (2024). Компонентный состав генофонда коренных этносов Дагестана. Biotekhnologiya. 40(6). 100–109.
4.
Мустафин, Р. Н. & Э. К. Хуснутдинова. (2024). The role of transposable elements in long-term memory formation. Генетика. 60(4). 3–19.
5.
Khidiyatova, I. M., I. M. Khidiyatova, Р. А. Зинченко, et al.. (2023). Study of The Molecular Nature of Congenital Cataracts in Patients from The Volga–Ural Region. Current Issues in Molecular Biology. 45(6). 5145–5163. 1 indexed citations
6.
Sakaeva, Dina, et al.. (2023). Whole Exome Sequencing Study Suggests an Impact of FANCA, CDH1 and VEGFA Genes on Diffuse Gastric Cancer Development. Genes. 14(2). 280–280. 1 indexed citations
7.
Ivanova, Elizaveta, et al.. (2023). Exosomal MicroRNA Levels Associated with Immune Checkpoint Inhibitor Therapy in Clear Cell Renal Cell Carcinoma. Biomedicines. 11(3). 801–801. 12 indexed citations
8.
Prokopenko, Inga, et al.. (2022). Using a Polygenic Score to Predict the Risk of Developing Primary Osteoporosis. International Journal of Molecular Sciences. 23(17). 10021–10021. 12 indexed citations
9.
Gilyazova, I. R., Elizaveta Ivanova, Mikhail Y. Sinelnikov, et al.. (2022). The potential of miR-153 as aggressive prostate cancer biomarker. Non-coding RNA Research. 8(1). 53–59. 6 indexed citations
10.
Мустафин, Р. Н. & Э. К. Хуснутдинова. (2020). Involvement of transposable elements in neurogenesis. Vavilov Journal of Genetics and Breeding. 24(2). 209–218. 13 indexed citations
11.
Мустафин, Р. Н. & Э. К. Хуснутдинова. (2019). The role of transposable elements in the ecological morphogenesis under the influence of stress. Vavilov Journal of Genetics and Breeding. 23(4). 380–389. 11 indexed citations
12.
Хусаинова, Р. И., et al.. (2018). Клинико-генетические аспекты кардиомиопатий. 17(12). 3–13. 1 indexed citations
13.
Казанцева, А. В., et al.. (2015). Genetic and environmental aspects of mathematical disabilities. Russian Journal of Genetics. 51(3). 223–230. 6 indexed citations
14.
Гареева, А. Э. & Э. К. Хуснутдинова. (2015). [Glutamate receptors genes polymorphism and the risk of paranoid schizophrenia in Russians and tatars from the Republic of Bashkortostan].. PubMed. 48(5). 771–81. 2 indexed citations
15.
Гареева, А. Э., et al.. (2015). Polymorphism of brain neurotransmitter system genes: Search for pharmacogenetic markers of haloperidol efficiency in Russians and Tatars. Molecular Biology. 49(6). 858–866. 6 indexed citations
16.
Fedorova, Yu. Yu., et al.. (2011). Association of ADAM33 gene polymorphisms with asthma in Volga-Ural region of Russia. European Respiratory Journal. 38(Suppl 55). p436–p436. 1 indexed citations
17.
Järve, Mari, Lev A. Zhivotovsky, Siiri Rootsi, et al.. (2009). Decreased Rate of Evolution in Y Chromosome STR Loci of Increased Size of the Repeat Unit. PLoS ONE. 4(9). e7276–e7276. 10 indexed citations
18.
Dzhemileva, Lilya U., et al.. (2008). Molecular genetic basis of tapetoretinal degeneration. Molecular Biology. 42(1). 1–8. 3 indexed citations
19.
Федорова, С.А., Р. И. Хусаинова, Ildus Kutuev, et al.. (2005). Polymorphism of the (CTG)n Repeat of the Myotonin Protein Kinase Gene in Populations of the Sakha Republic (Yakutia) and Central Asia. Molecular Biology. 39(3). 341–349. 4 indexed citations
20.
Ахметова, В. Р., et al.. (2000). Molecular genetic analysis of the VNTR polymorphism at the phenylalanine hydroxylase gene in populations of the Volga-Ural region. Genetika. 36(8). 1161–1165. 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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