Natalia Ivanova

4.6k total citations · 2 hit papers
34 papers, 2.8k citations indexed

About

Natalia Ivanova is a scholar working on Molecular Biology, Condensed Matter Physics and Electronic, Optical and Magnetic Materials. According to data from OpenAlex, Natalia Ivanova has authored 34 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 12 papers in Condensed Matter Physics and 9 papers in Electronic, Optical and Magnetic Materials. Recurrent topics in Natalia Ivanova's work include Advanced Condensed Matter Physics (11 papers), Pluripotent Stem Cells Research (9 papers) and Crystal Structures and Properties (9 papers). Natalia Ivanova is often cited by papers focused on Advanced Condensed Matter Physics (11 papers), Pluripotent Stem Cells Research (9 papers) and Crystal Structures and Properties (9 papers). Natalia Ivanova collaborates with scholars based in United States, Russia and Canada. Natalia Ivanova's co-authors include Zheng Wang, P. F. L. Maxted, Philipp Podsiadlowski, T. R. Marsh, Zhanwen Han, Efrat Oron, Ihor R. Lemischka, John T. Dimos, Sally Temple and Timothy N. Phoenix and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Natalia Ivanova

30 papers receiving 2.8k citations

Hit Papers

Visualizing structure an... 2002 2026 2010 2018 2019 2002 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Natalia Ivanova United States 18 1.6k 494 301 246 220 34 2.8k
H. R. Russell United States 42 1.8k 1.2× 2.3k 4.7× 109 0.4× 293 1.2× 196 0.9× 109 4.5k
С. А. Кузнецов Russia 31 830 0.5× 166 0.3× 30 0.1× 119 0.5× 56 0.3× 264 3.5k
Christopher Hunter United States 25 457 0.3× 799 1.6× 47 0.2× 62 0.3× 177 0.8× 71 2.8k
Daisuke Yamazaki Japan 39 1.2k 0.7× 73 0.1× 30 0.1× 85 0.3× 139 0.6× 178 4.9k
Daniel Côté Canada 33 1.2k 0.8× 23 0.0× 120 0.4× 114 0.5× 366 1.7× 79 5.7k
W Mansfield United States 27 3.2k 2.0× 33 0.1× 68 0.2× 532 2.2× 145 0.7× 96 4.5k
Sylvain V. Costes United States 34 2.9k 1.9× 67 0.1× 111 0.4× 263 1.1× 700 3.2× 110 5.4k
Clive Standley United States 18 983 0.6× 38 0.1× 19 0.1× 131 0.5× 255 1.2× 32 1.4k
Ullrich Koethe Germany 12 830 0.5× 31 0.1× 25 0.1× 76 0.3× 46 0.2× 26 2.3k
Jan Huisken Germany 38 3.3k 2.1× 5 0.0× 59 0.2× 237 1.0× 148 0.7× 89 7.5k

Countries citing papers authored by Natalia Ivanova

Since Specialization
Citations

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

Fields of papers citing papers by Natalia Ivanova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natalia Ivanova

This figure shows the co-authorship network connecting the top 25 collaborators of Natalia Ivanova. A scholar is included among the top collaborators of Natalia Ivanova 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 Natalia Ivanova. Natalia Ivanova 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.
Saito‐Diaz, Kenyi, Fabio R. Santori, Smita Krishnaswamy, et al.. (2024). Parasympathetic neurons derived from human pluripotent stem cells model human diseases and development. Cell stem cell. 31(5). 734–753.e8. 7 indexed citations
2.
Moon, Kevin R., David van Dijk, Zheng Wang, et al.. (2020). Author Correction: Visualizing structure and transitions in high-dimensional biological data. Nature Biotechnology. 38(1). 108–108. 6 indexed citations
3.
Jackson, Ben, et al.. (2020). Nuclear Hormone Receptors and Their Ligands: Metabolites in Control of Transcription. Cells. 9(12). 2606–2606. 22 indexed citations
4.
Moon, Kevin R., David van Dijk, Zheng Wang, et al.. (2019). Visualizing structure and transitions in high-dimensional biological data. Nature Biotechnology. 37(12). 1482–1492. 524 indexed citations breakdown →
5.
Ivanova, Natalia, Carlos‐Filipe Pereira, & Dung‐Fang Lee. (2018). Ihor R. Lemischka (1953–2017). Cell. 172(1-2). 1–2. 17 indexed citations
6.
Wang, Zheng, Bulat R. Ramazanov, Yin Tang, et al.. (2018). Dppa2/4 Facilitate Epigenetic Remodeling during Reprogramming to Pluripotency. Cell stem cell. 23(3). 396–411.e8. 48 indexed citations
7.
Wang, Zheng, Micah D. Gearhart, Ishan Kumar, et al.. (2018). A Non-canonical BCOR-PRC1.1 Complex Represses Differentiation Programs in Human ESCs. Cell stem cell. 22(2). 235–251.e9. 65 indexed citations
8.
Moon, Kevin R., David van Dijk, Zheng Wang, et al.. (2018). Visualizing Structure and Transitions for Biological Data Exploration. SSRN Electronic Journal. 10 indexed citations
9.
Benitah, Salvador Aznar, Adrian P. Bracken, Yali Dou, et al.. (2014). Stem Cell Epigenetics: Looking Forward. Cell stem cell. 14(6). 706–709.
10.
Zhang, Ying, Vincent Schulz, Brian D. Reed, et al.. (2013). Functional genomic screen of human stem cell differentiation reveals pathways involved in neurodevelopment and neurodegeneration. Proceedings of the National Academy of Sciences. 110(30). 12361–12366. 20 indexed citations
11.
Oron, Efrat & Natalia Ivanova. (2012). Cell fate regulation in early mammalian development. Physical Biology. 9(4). 45002–45002. 27 indexed citations
12.
Wang, Zheng, et al.. (2012). Distinct Lineage Specification Roles for NANOG, OCT4, and SOX2 in Human Embryonic Stem Cells. Cell stem cell. 10(4). 440–454. 411 indexed citations
13.
Ivanova, Natalia, et al.. (2007). Magnetic and electrical properties of cobalt oxyborate Co3BO5. Physics of the Solid State. 49(4). 651–653. 28 indexed citations
14.
Ivanova, Natalia, et al.. (2007). Structure probing of tmRNA in distinct stages of trans-translation. RNA. 13(5). 713–722. 17 indexed citations
15.
Shen, Qin, Yue Wang, John T. Dimos, et al.. (2006). The timing of cortical neurogenesis is encoded within lineages of individual progenitor cells. Nature Neuroscience. 9(6). 743–751. 463 indexed citations
16.
Ivanova, Natalia, Michael Y. Pavlov, Brice Felden, & Måns Ehrenberg. (2004). Ribosome Rescue by tmRNA Requires Truncated mRNAs. Journal of Molecular Biology. 338(1). 33–41. 97 indexed citations
17.
Balaev, А. D., et al.. (2003). Magnetic anisotropy of the VBO3 and CrBO3 transition-metal borates. Physics of the Solid State. 45(2). 287–291. 10 indexed citations
18.
Haan, Gerald de, Leonid Bystrykh, Ellen Weersing, et al.. (2002). A genetic and genomic analysis identifies a cluster of genes associated with hematopoietic cell turnover. Blood. 100(6). 2056–2062. 51 indexed citations
19.
Balaev, А. D., et al.. (1997). Quantum oscillations of resistance and magnetization in magnetic semiconductors and semimetals. Physics-Uspekhi. 40(9). 966–969. 1 indexed citations
20.
Simonov, V. I., А. D. Balaev, V. V. Val’kov, et al.. (1997). Scientific session of the Division of General Physics and Astronomy of the Russian Academy of Sciences (April 23, 1997). Physics-Uspekhi. 40(9). 963–974. 6 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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