Natacha Shaw

1.9k total citations · 1 hit paper
9 papers, 1.6k citations indexed

About

Natacha Shaw is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Ophthalmology. According to data from OpenAlex, Natacha Shaw has authored 9 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Cellular and Molecular Neuroscience and 2 papers in Ophthalmology. Recurrent topics in Natacha Shaw's work include Retinoids in leukemia and cellular processes (6 papers), Peroxisome Proliferator-Activated Receptors (5 papers) and Retinal Development and Disorders (3 papers). Natacha Shaw is often cited by papers focused on Retinoids in leukemia and cellular processes (6 papers), Peroxisome Proliferator-Activated Receptors (5 papers) and Retinal Development and Disorders (3 papers). Natacha Shaw collaborates with scholars based in United States, Switzerland and Sweden. Natacha Shaw's co-authors include Noa Noy, Daniel C. Berry, Thaddeus T. Schug, Morten Elholm, Nguan Soon Tan, Rubina Yasmin, Nicolas Vinckenbosch, Peng Liu, Béatrice Desvergne and Walter Wahli and has published in prestigious journals such as Cell, Journal of Biological Chemistry and Molecular and Cellular Biology.

In The Last Decade

Natacha Shaw

9 papers receiving 1.5k citations

Hit Papers

Opposing Effects of Retinoic Acid on Cell Growth Result f... 2007 2026 2013 2019 2007 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
Natacha Shaw United States 9 1.2k 271 211 210 185 9 1.6k
Vivian E.H. Dahlmans Netherlands 22 843 0.7× 398 1.5× 268 1.3× 123 0.6× 118 0.6× 34 1.7k
Thomas Åskov Pedersen Denmark 17 1.1k 0.9× 315 1.2× 165 0.8× 126 0.6× 172 0.9× 28 1.7k
Simone Kaiser Germany 16 629 0.5× 145 0.5× 124 0.6× 151 0.7× 69 0.4× 21 1.3k
Hiroshi Kuwata Japan 20 1.1k 0.9× 250 0.9× 387 1.8× 208 1.0× 198 1.1× 43 1.9k
Louisa Balázs United States 20 1.1k 0.9× 259 1.0× 131 0.6× 303 1.4× 87 0.5× 39 1.7k
Li‐Shin Huang United States 26 1.2k 1.0× 441 1.6× 264 1.3× 393 1.9× 322 1.7× 39 2.8k
Yasuomi Urano Japan 22 996 0.8× 411 1.5× 195 0.9× 112 0.5× 48 0.3× 47 1.8k
Marc L. Goalstone United States 22 1.0k 0.8× 454 1.7× 177 0.8× 107 0.5× 91 0.5× 44 1.9k
Mei‐Zhen Cui United States 27 1.1k 0.9× 487 1.8× 163 0.8× 272 1.3× 59 0.3× 54 1.8k
Paul Van Veldhoven Belgium 16 1.0k 0.8× 265 1.0× 323 1.5× 86 0.4× 91 0.5× 25 1.6k

Countries citing papers authored by Natacha Shaw

Since Specialization
Citations

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

Fields of papers citing papers by Natacha Shaw

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Natacha Shaw

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

All Works

9 of 9 papers shown
1.
Schug, Thaddeus T., et al.. (2007). Opposing Effects of Retinoic Acid on Cell Growth Result from Alternate Activation of Two Different Nuclear Receptors. Cell. 129(4). 723–733. 557 indexed citations breakdown →
2.
Wu, Zhiping, Yanwu Yang, Natacha Shaw, et al.. (2003). Mapping the Ligand Binding Pocket in the Cellular Retinaldehyde Binding Protein. Journal of Biological Chemistry. 278(14). 12390–12396. 14 indexed citations
3.
Golovleva, Irina, Sanjoy K. Bhattacharya, Zhiping Wu, et al.. (2003). Disease-causing Mutations in the Cellular Retinaldehyde Binding Protein Tighten and Abolish Ligand Interactions. Journal of Biological Chemistry. 278(14). 12397–12402. 57 indexed citations
4.
Shaw, Natacha, Morten Elholm, & Noa Noy. (2003). Retinoic Acid Is a High Affinity Selective Ligand for the Peroxisome Proliferator-activated Receptor β/δ. Journal of Biological Chemistry. 278(43). 41589–41592. 207 indexed citations
5.
Tan, Nguan Soon, et al.. (2002). Selective Cooperation between Fatty Acid Binding Proteins and Peroxisome Proliferator-Activated Receptors in Regulating Transcription. Molecular and Cellular Biology. 22(17). 6318–6318. 39 indexed citations
7.
Tan, Nguan Soon, Natacha Shaw, Nicolas Vinckenbosch, et al.. (2002). Selective Cooperation between Fatty Acid Binding Proteins and Peroxisome Proliferator-Activated Receptors in Regulating Transcription. Molecular and Cellular Biology. 22(14). 5114–5127. 401 indexed citations
8.
Shaw, Natacha & Noa Noy. (2001). Interphotoreceptor Retinoid-binding Protein Contains Three Retinoid Binding Sites. Experimental Eye Research. 72(2). 183–190. 20 indexed citations
9.
Lin, Qiong, et al.. (1998). Ligand Selectivity of the Peroxisome Proliferator-Activated Receptor α. Biochemistry. 38(1). 185–190. 223 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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