Alexey Sergushichev

11.3k total citations · 3 hit papers
47 papers, 4.2k citations indexed

About

Alexey Sergushichev is a scholar working on Molecular Biology, Immunology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Alexey Sergushichev has authored 47 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Molecular Biology, 9 papers in Immunology and 8 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Alexey Sergushichev's work include Bioinformatics and Genomic Networks (7 papers), Immune cells in cancer (6 papers) and Cardiomyopathy and Myosin Studies (5 papers). Alexey Sergushichev is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Immune cells in cancer (6 papers) and Cardiomyopathy and Myosin Studies (5 papers). Alexey Sergushichev collaborates with scholars based in Russia, United States and Sweden. Alexey Sergushichev's co-authors include Maxim N. Artyomov, Ekaterina Loginicheva, Stanley Ching‐Cheng Huang, Edward J. Pearce, Vicky Lampropoulou, Abhishek Jha, Edward M. Driggers, Bart Everts, Kelly M. Stewart and Yulia Ivanova and has published in prestigious journals such as Nature, Cell and Nucleic Acids Research.

In The Last Decade

Alexey Sergushichev

42 papers receiving 4.2k citations

Hit Papers

Network Integration of Parallel Metabolic and Transcripti... 2015 2026 2018 2022 2015 2016 2017 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alexey Sergushichev Russia 13 2.1k 1.9k 833 612 582 47 4.2k
Ekaterina Loginicheva United States 9 2.0k 1.0× 1.7k 0.9× 828 1.0× 579 0.9× 538 0.9× 9 3.9k
Luisa Klotz Germany 38 1.7k 0.8× 1.6k 0.9× 679 0.8× 397 0.6× 239 0.4× 162 4.9k
Paqui G. Través Spain 25 1.9k 0.9× 1.2k 0.6× 431 0.5× 572 0.9× 393 0.7× 43 3.6k
Gopal Murugaiyan United States 30 2.0k 0.9× 1.1k 0.6× 490 0.6× 382 0.6× 624 1.1× 44 4.0k
Eva Tolosa Germany 36 2.5k 1.2× 1.5k 0.8× 1.3k 1.6× 259 0.4× 436 0.7× 98 5.5k
Guang‐Xian Zhang United States 44 4.2k 2.0× 1.8k 1.0× 1.1k 1.3× 488 0.8× 503 0.9× 157 7.2k
Janine M. van Gils Netherlands 22 1.5k 0.7× 1.9k 1.0× 355 0.4× 354 0.6× 1.1k 1.8× 38 4.2k
Bao‐Guo Xiao China 41 1.8k 0.9× 1.2k 0.7× 1.1k 1.4× 602 1.0× 162 0.3× 221 5.3k
Matthias Klein Germany 31 2.3k 1.1× 850 0.5× 767 0.9× 593 1.0× 220 0.4× 67 3.9k
Michael Fricker Australia 33 1.1k 0.5× 1.5k 0.8× 745 0.9× 1.1k 1.8× 248 0.4× 71 4.1k

Countries citing papers authored by Alexey Sergushichev

Since Specialization
Citations

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

Fields of papers citing papers by Alexey Sergushichev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Alexey Sergushichev

This figure shows the co-authorship network connecting the top 25 collaborators of Alexey Sergushichev. A scholar is included among the top collaborators of Alexey Sergushichev 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 Alexey Sergushichev. Alexey Sergushichev 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.
Artyomov, Maxim N., et al.. (2024). Phantasus, a web application for visual and interactive gene expression analysis. eLife. 13. 12 indexed citations
2.
Artomov, Mykyta, et al.. (2024). Application of Markov chain Monte Carlo and machine learning for identifying active modules in biological graphs. SHILAP Revista de lepidopterología. 24(6). 962–971.
3.
Njauw, Ching-Ni Jenny, Zhenyu Ji, Alexey Sergushichev, et al.. (2024). Analysis of Variants Induced by Combined Ex Vivo Irradiation and In Vivo Tumorigenesis Suggests a Role for the ZNF831 p.R1393Q Variant in Cutaneous Melanoma Development. Journal of Investigative Dermatology. 145(7). 1728–1739.e7.
4.
Firulyova, Maria, Alexey Sergushichev, Л. Б. Митрофанова, et al.. (2024). Molecular effects of cardiac contractility modulation in patients with heart failure of ischemic aetiology uncovered by transcriptome analysis. Frontiers in Cardiovascular Medicine. 11. 1321005–1321005. 3 indexed citations
5.
Yermakovich, Danat, E. D. Kasyanov, Г. В. Рукавишников, et al.. (2023). GWAS of depression in 4,520 individuals from the Russian population highlights the role of MAGI2 (S-SCAM) in the gut-brain axis. Frontiers in Genetics. 13. 972196–972196. 6 indexed citations
6.
Loboda, Alexander, et al.. (2023). Gene, cell type, and drug prioritization analysis suggest genetic basis for the utility of diuretics in treating Alzheimer disease. Human Genetics and Genomics Advances. 4(3). 100203–100203. 2 indexed citations
7.
Mogilenko, Denis A., Alexey Sergushichev, & Maxim N. Artyomov. (2023). Systems Immunology Approaches to Metabolism. Annual Review of Immunology. 41(1). 317–342. 12 indexed citations
8.
Santeford, Andrea, Aaron Lee, Abdoulaye Sène, et al.. (2021). Loss of Mir146b with aging contributes to inflammation and mitochondrial dysfunction in thioglycollate-elicited peritoneal macrophages. eLife. 10. 10 indexed citations
9.
12.
Kostareva, Anna, et al.. (2019). Clinical Response to Personalized Exercise Therapy in Heart Failure Patients with Reduced Ejection Fraction Is Accompanied by Skeletal Muscle Histological Alterations. International Journal of Molecular Sciences. 20(21). 5514–5514. 3 indexed citations
13.
14.
Pelgrom, Leonard R., Thiago A. Patente, Alexey Sergushichev, et al.. (2019). LKB1 expressed in dendritic cells governs the development and expansion of thymus-derived regulatory T cells. Cell Research. 29(5). 406–419. 34 indexed citations
16.
Ulland, Tyler K., Wilbur M. Song, Stanley Ching‐Cheng Huang, et al.. (2017). TREM2 Maintains Microglial Metabolic Fitness in Alzheimer’s Disease. Cell. 170(4). 649–663.e13. 823 indexed citations breakdown →
17.
Derr, Alan, Chaoxing Yang, Rapolas Žilionis, et al.. (2016). End Sequence Analysis Toolkit (ESAT) expands the extractable information from single-cell RNA-seq data. Genome Research. 26(10). 1397–1410. 33 indexed citations
18.
Izreig, Said, Bożena Samborska, Radia Marie Johnson, et al.. (2016). The miR-17∼92 microRNA Cluster Is a Global Regulator of Tumor Metabolism. Cell Reports. 16(7). 1915–1928. 52 indexed citations
19.
Glotov, Аndrey S., С. В. Казаков, Елена Жукова, et al.. (2015). Targeted next-generation sequencing (NGS) of nine candidate genes with custom AmpliSeq in patients and a cardiomyopathy risk group. Clinica Chimica Acta. 446. 132–140. 24 indexed citations
20.
Vincent, Emma E., Alexey Sergushichev, Takla Griss, et al.. (2015). Mitochondrial Phosphoenolpyruvate Carboxykinase Regulates Metabolic Adaptation and Enables Glucose-Independent Tumor Growth. Molecular Cell. 60(2). 195–207. 204 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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