Sergey Kisselev

2.0k total citations
17 papers, 772 citations indexed

About

Sergey Kisselev is a scholar working on Molecular Biology, Neurology and Physiology. According to data from OpenAlex, Sergey Kisselev has authored 17 papers receiving a total of 772 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 5 papers in Neurology and 4 papers in Physiology. Recurrent topics in Sergey Kisselev's work include Neurological disorders and treatments (4 papers), Glycogen Storage Diseases and Myoclonus (3 papers) and Parkinson's Disease Mechanisms and Treatments (3 papers). Sergey Kisselev is often cited by papers focused on Neurological disorders and treatments (4 papers), Glycogen Storage Diseases and Myoclonus (3 papers) and Parkinson's Disease Mechanisms and Treatments (3 papers). Sergey Kisselev collaborates with scholars based in United States, Belgium and Canada. Sergey Kisselev's co-authors include Lorraine N. Clark, Joseph H. Lee, Karen Marder, Stanley Fahn, Miguel Verbitsky, Eric Siddall, Pietro A. Canetta, Howard Andrews, Lucien Côté and Thomas L. Nickolas and has published in prestigious journals such as PLoS ONE, Neurobiology of Aging and Journal of the American Medical Informatics Association.

In The Last Decade

Sergey Kisselev

16 papers receiving 763 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sergey Kisselev United States 14 394 189 177 126 124 17 772
Carlos Casasnovas Spain 14 179 0.5× 43 0.2× 270 1.5× 31 0.2× 149 1.2× 40 567
Carl Fratter United Kingdom 26 151 0.4× 158 0.8× 945 5.3× 19 0.2× 141 1.1× 47 1.3k
Slobodan Apostolski Serbia 18 990 2.5× 95 0.5× 270 1.5× 140 1.1× 287 2.3× 63 1.4k
Kenichi Kaida Japan 21 991 2.5× 104 0.6× 140 0.8× 64 0.5× 735 5.9× 71 1.2k
S. Lane Rutledge United States 19 129 0.3× 104 0.6× 844 4.8× 30 0.2× 295 2.4× 31 1.3k
Susana Teijeira Spain 16 109 0.3× 192 1.0× 305 1.7× 26 0.2× 120 1.0× 38 689
Yaqing Shu China 16 179 0.5× 49 0.3× 282 1.6× 41 0.3× 44 0.4× 47 689
José Luís Muñoz-Blanco Spain 11 568 1.4× 65 0.3× 128 0.7× 133 1.1× 120 1.0× 27 712
Ronald I. Jacobson United States 9 61 0.2× 403 2.1× 252 1.4× 47 0.4× 65 0.5× 13 790
Xiaopan Wu China 18 44 0.1× 67 0.4× 219 1.2× 45 0.4× 81 0.7× 38 829

Countries citing papers authored by Sergey Kisselev

Since Specialization
Citations

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

Fields of papers citing papers by Sergey Kisselev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sergey Kisselev

This figure shows the co-authorship network connecting the top 25 collaborators of Sergey Kisselev. A scholar is included among the top collaborators of Sergey Kisselev 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 Sergey Kisselev. Sergey Kisselev 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.
Turchioe, Meghan Reading, Sergey Kisselev, Liesbet Van Bulck, & Suzanne Bakken. (2024). Increasing Generative Artificial Intelligence Competency among Students Enrolled in Doctoral Nursing Research Coursework. Applied Clinical Informatics. 15(5). 842–851. 6 indexed citations
2.
Turchioe, Meghan Reading, et al.. (2024). Returning value from the All of Us Research Program to PhD-level nursing students using ChatGPT as programming support: results from a mixed-methods experimental feasibility study. Journal of the American Medical Informatics Association. 31(12). 2974–2979. 5 indexed citations
3.
Bakken, Suzanne, Caitlin Dreisbach, Sergey Kisselev, & Meghan Reading Turchioe. (2024). Advancing Data Science Competencies for Nursing PhD Students. Studies in health technology and informatics. 315. 515–519.
4.
Peleg, Yonatan, Satoru Kudose, Vivette D. D’Agati, et al.. (2020). Acute Kidney Injury Due to Collapsing Glomerulopathy Following COVID-19 Infection. Kidney International Reports. 5(6). 940–945. 167 indexed citations
5.
Lee, Joseph H., Annie Lee, Deborah Pang, et al.. (2017). Candidate gene analysis for Alzheimer's disease in adults with Down syndrome. Neurobiology of Aging. 56. 150–158. 16 indexed citations
6.
Hernández, Nora, Sergey Kisselev, Aris Floratos, et al.. (2015). Identification of candidate genes for familial early-onset essential tremor. European Journal of Human Genetics. 24(7). 1009–1015. 34 indexed citations
7.
Schupf, Nicole, Annie Lee, Naeun Park, et al.. (2015). Candidate genes for Alzheimer's disease are associated with individual differences in plasma levels of beta amyloid peptides in adults with Down syndrome. Neurobiology of Aging. 36(10). 2907.e1–2907.e10. 26 indexed citations
8.
Clark, Lorraine N., Robin Chan, Rong Cheng, et al.. (2015). Gene-Wise Association of Variants in Four Lysosomal Storage Disorder Genes in Neuropathologically Confirmed Lewy Body Disease. PLoS ONE. 10(5). e0125204–e0125204. 52 indexed citations
9.
Green, Nancy, Farzana Pashankar, Catherine Driscoll, et al.. (2013). Candidate Sequence Variants and Fetal Hemoglobin in Children with Sickle Cell Disease Treated with Hydroxyurea. PLoS ONE. 8(2). e55709–e55709. 25 indexed citations
10.
Narayan, Gopeshwar, Dongxu Xie, Allen J. Freddy, et al.. (2013). PCDH10 promoter hypermethylation is frequent in most histologic subtypes of mature lymphoid malignancies and occurs early in lymphomagenesis. Genes Chromosomes and Cancer. 52(11). 1030–1041. 15 indexed citations
11.
Liu, Xinmin, Rong Cheng, Xin Ye, et al.. (2013). Increased rate of sporadic and recurrent rare genic copy number variants in Parkinson's disease among Ashkenazi Jews. Molecular Genetics & Genomic Medicine. 1(3). 142–154. 20 indexed citations
12.
Parmalee, Nancy L., Sergey Kisselev, Nancy D. Merner, et al.. (2012). Genetic analysis of the FUS/TLS gene in essential tremor. European Journal of Neurology. 20(3). 534–539. 27 indexed citations
13.
Narayan, Gopeshwar, Allen J. Freddy, Dongxu Xie, et al.. (2011). Promoter methylation‐mediated inactivation of PCDH10 in acute lymphoblastic leukemia contributes to chemotherapy resistance. Genes Chromosomes and Cancer. 50(12). 1043–1053. 27 indexed citations
14.
Liu, Xinmin, Rong Cheng, Miguel Verbitsky, et al.. (2011). Genome-Wide association study identifies candidate genes for Parkinson's disease in an Ashkenazi Jewish population. BMC Medical Genetics. 12(1). 104–104. 133 indexed citations
15.
Clark, Lorraine N., Naeun Park, Sergey Kisselev, et al.. (2010). Replication of the LINGO1 gene association with essential tremor in a North American population. European Journal of Human Genetics. 18(7). 838–843. 54 indexed citations
16.
Clark, Lorraine N., Sergey Kisselev, Naeun Park, et al.. (2009). Mutations in the Parkinson's disease genes, Leucine Rich Repeat Kinase 2 (LRRK2) and Glucocerebrosidase (GBA), are not associated with essential tremor. Parkinsonism & Related Disorders. 16(2). 132–135. 26 indexed citations
17.
Clark, Lorraine N., Rebecca Gilbert, Beatriz Dorado, et al.. (2009). Association of Glucocerebrosidase Mutations With Dementia With Lewy Bodies. Archives of Neurology. 66(5). 578–83. 139 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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