Natalya Perelman

1.0k total citations
8 papers, 833 citations indexed

About

Natalya Perelman is a scholar working on Molecular Biology, Genetics and Infectious Diseases. According to data from OpenAlex, Natalya Perelman has authored 8 papers receiving a total of 833 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Infectious Diseases. Recurrent topics in Natalya Perelman's work include Virus-based gene therapy research (3 papers), CRISPR and Genetic Engineering (3 papers) and Viral gastroenteritis research and epidemiology (2 papers). Natalya Perelman is often cited by papers focused on Virus-based gene therapy research (3 papers), CRISPR and Genetic Engineering (3 papers) and Viral gastroenteritis research and epidemiology (2 papers). Natalya Perelman collaborates with scholars based in United States, Taiwan and Italy. Natalya Perelman's co-authors include Punam Malik, Vijay K. Kalra, Marcel E. Nimni, Ranjit K. Giri, Cage S. Johnson, Sandeep Batra, Suresh Selvaraj, David T. Cheung, Ping Xia and Hiroyuki Shimada and has published in prestigious journals such as Blood, Journal of Biomedical Materials Research and Molecular Therapy.

In The Last Decade

Natalya Perelman

8 papers receiving 807 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Natalya Perelman United States	7	367	196	181	163	99	8	833
Elaine Herer Canada	11	278 0.8×	136 0.7×	203 1.1×	40 0.2×	129 1.3×	19	856
Jennifer O. Manilay United States	15	453 1.2×	228 1.2×	74 0.4×	74 0.5×	123 1.2×	31	1000
B C Adelmann-Grill Germany	19	158 0.4×	69 0.4×	46 0.3×	101 0.6×	107 1.1×	32	1.1k
G P Bagnara Italy	13	252 0.7×	155 0.8×	176 1.0×	45 0.3×	96 1.0×	22	679
Sandra Bordin United States	14	311 0.8×	78 0.4×	128 0.7×	86 0.5×	112 1.1×	29	1.1k
Terumasa Umemoto Japan	21	371 1.0×	344 1.8×	124 0.7×	78 0.5×	109 1.1×	43	1.1k
Janet M. Kerr United States	14	762 2.1×	83 0.4×	451 2.5×	170 1.0×	218 2.2×	16	1.7k
Lindsay C. Davies Sweden	19	382 1.0×	125 0.6×	820 4.5×	88 0.5×	449 4.5×	41	1.5k
Martin Ryser Germany	15	297 0.8×	114 0.6×	141 0.8×	85 0.5×	58 0.6×	28	594
Mónica S. Ventura Ferreira Germany	16	221 0.6×	363 1.9×	367 2.0×	29 0.2×	110 1.1×	31	823

Countries citing papers authored by Natalya Perelman

Since Specialization

Citations

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

Fields of papers citing papers by Natalya Perelman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natalya Perelman

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

All Works

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8 of 8 papers shown

Arumugam, Paritha, Jessica Scholes, Natalya Perelman, et al.. (2007). Improved Human β-globin Expression from Self-inactivating Lentiviral Vectors Carrying the Chicken Hypersensitive Site-4 (cHS4) Insulator Element. Molecular Therapy. 15(10). 1863–1871. 92 indexed citations

Arumugam, Paritha, et al.. (2005). Self-Inactivating Lentiviral Vectors Flanked by a Chromatin Insulator Element Result in Increased, Consistent Expression of Human Beta Globin.. Blood. 106(11). 527–527. 3 indexed citations

Selvaraj, Suresh, Ranjit K. Giri, Natalya Perelman, et al.. (2003). Mechanism of monocyte activation and expression of proinflammatory cytochemokines by placenta growth factor. Blood. 102(4). 1515–1524. 229 indexed citations

Batra, Sandeep, et al.. (2003). Pediatric Tumor Cells Express Erythropoietin and a Functional Erythropoietin Receptor that Promotes Angiogenesis and Tumor Cell Survival. Laboratory Investigation. 83(10). 1477–1487. 106 indexed citations

Perelman, Natalya, Sandeep Batra, Anat Erdreich‐Epstein, et al.. (2003). Placenta growth factor activates monocytes and correlates with sickle cell disease severity. Blood. 102(4). 1506–1514. 133 indexed citations

Han, Bo, et al.. (2002). Collagen‐targeted BMP3 fusion proteins arrayed on collagen matrices or porous ceramics impregnated with Type I collagen enhance osteogenesis in a rat cranial defect model. Journal of Orthopaedic Research®. 20(4). 747–755. 36 indexed citations

Moreau‐Gaudry, François, Ping Xia, Gang Jiang, et al.. (2001). High-level erythroid-specific gene expression in primary human and murine hematopoietic cells with self-inactivating lentiviral vectors. Blood. 98(9). 2664–2672. 100 indexed citations

Cheung, David T., et al.. (1990). The effect of γ‐irradiation on collagen molecules, isolated α‐chains, and crosslinked native fibers. Journal of Biomedical Materials Research. 24(5). 581–589. 134 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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