Yuko Williams

509 total citations
9 papers, 417 citations indexed

About

Yuko Williams is a scholar working on Molecular Biology, Physiology and Surgery. According to data from OpenAlex, Yuko Williams has authored 9 papers receiving a total of 417 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Physiology and 2 papers in Surgery. Recurrent topics in Yuko Williams's work include Erythrocyte Function and Pathophysiology (5 papers), Renal and related cancers (4 papers) and Epigenetics and DNA Methylation (2 papers). Yuko Williams is often cited by papers focused on Erythrocyte Function and Pathophysiology (5 papers), Renal and related cancers (4 papers) and Epigenetics and DNA Methylation (2 papers). Yuko Williams collaborates with scholars based in Japan, United States and United Kingdom. Yuko Williams's co-authors include Mari Masuda, Yoshinori Murakami, Tomoko Maruyama, Mika Sakurai‐Yageta, Shinji Kikuchi, Takeshi Fukami, Tadaichi Kitamura, Daisuke Yamada, Joon Kim and Carrie M Louie and has published in prestigious journals such as Journal of Biological Chemistry, Nature Medicine and Molecular and Cellular Biology.

In The Last Decade

Yuko Williams

9 papers receiving 416 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yuko Williams Japan 7 309 105 60 53 43 9 417
Prasuna Paluru United States 17 334 1.1× 104 1.0× 32 0.5× 40 0.8× 77 1.8× 20 889
Raimund Fahsold Germany 14 344 1.1× 159 1.5× 84 1.4× 50 0.9× 130 3.0× 27 777
Karine Sii-Felice France 14 418 1.4× 99 0.9× 30 0.5× 53 1.0× 27 0.6× 17 589
Ji Yoo Kim Japan 9 321 1.0× 62 0.6× 25 0.4× 34 0.6× 30 0.7× 13 446
Inger M. Olsen Denmark 8 227 0.7× 72 0.7× 21 0.3× 50 0.9× 16 0.4× 10 488
Martha Kalff-Suske Germany 10 312 1.0× 159 1.5× 18 0.3× 51 1.0× 27 0.6× 15 475
Jens Böse Germany 8 714 2.3× 187 1.8× 50 0.8× 28 0.5× 24 0.6× 8 839
Bert Eussen Netherlands 11 317 1.0× 92 0.9× 56 0.9× 28 0.5× 25 0.6× 18 569
Edoardo Errichiello Italy 11 177 0.6× 93 0.9× 31 0.5× 22 0.4× 32 0.7× 37 319
Martina Klempt Germany 12 235 0.8× 86 0.8× 22 0.4× 56 1.1× 12 0.3× 18 397

Countries citing papers authored by Yuko Williams

Since Specialization
Citations

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

Fields of papers citing papers by Yuko Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yuko Williams

This figure shows the co-authorship network connecting the top 25 collaborators of Yuko Williams. A scholar is included among the top collaborators of Yuko Williams 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 Yuko Williams. Yuko Williams 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.
Williams, Yuko, et al.. (2016). Single‐cell biomarker detection identifies heterogeneity within cancer populations. The FASEB Journal. 30(S1). 2 indexed citations
2.
Lancaster, Madeline A., Joon Kim, Sahar N. Saleem, et al.. (2011). Defective Wnt-dependent cerebellar midline fusion in a mouse model of Joubert syndrome. Nature Medicine. 17(6). 726–731. 114 indexed citations
3.
Yamada, Daisuke, Midori Yoshida, Yuko Williams, et al.. (2006). Disruption of Spermatogenic Cell Adhesion and Male Infertility in Mice Lacking TSLC1/IGSF4, an Immunoglobulin Superfamily Cell Adhesion Molecule. Molecular and Cellular Biology. 26(9). 3610–3624. 84 indexed citations
4.
Williams, Yuko, Mari Masuda, Mika Sakurai‐Yageta, et al.. (2005). Cell adhesion and prostate tumor-suppressor activity of TSLL2/IGSF4C, an immunoglobulin superfamily molecule homologous to TSLC1/IGSF4. Oncogene. 25(10). 1446–1453. 44 indexed citations
5.
Masuda, Mari, Shinji Kikuchi, Tomoko Maruyama, et al.. (2005). Tumor Suppressor in Lung Cancer (TSLC)1 Suppresses Epithelial Cell Scattering and Tubulogenesis. Journal of Biological Chemistry. 280(51). 42164–42171. 30 indexed citations
6.
Kikuchi, Shinji, Daisuke Yamada, Takeshi Fukami, et al.. (2005). Promoter Methylation of DAL-1/4.1B Predicts Poor Prognosis in Non–Small Cell Lung Cancer. Clinical Cancer Research. 11(8). 2954–2961. 66 indexed citations
7.
Yamada, Daisuke, Shinji Kikuchi, Yuko Williams, et al.. (2005). Promoter hypermethylation of the potential tumor suppressor DAL‐1/4.1B gene in renal clear cell carcinoma. International Journal of Cancer. 118(4). 916–923. 63 indexed citations
8.
Fukami, Takeshi, Hitoshi Satoh, Yuko Williams, et al.. (2003). Isolation of the mouse Tsll1 and Tsll2 genes, orthologues of the human TSLC1-like genes 1 and 2 (TSLL1 and TSLL2). Gene. 323. 11–18. 13 indexed citations
9.
Fukami, Tatsuki, H. Satoh, Yuko Williams, et al.. (2003). Isolation of the mouse Tsll1 and Tsll2 genes, orthologues of the human TSLC1-like genes 1 and 2. 323. 11–18. 1 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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