Ryan Vander Werff

1.1k total citations · 1 hit paper
7 papers, 756 citations indexed

About

Ryan Vander Werff is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Genetics. According to data from OpenAlex, Ryan Vander Werff has authored 7 papers receiving a total of 756 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Pulmonary and Respiratory Medicine and 1 paper in Genetics. Recurrent topics in Ryan Vander Werff's work include Pluripotent Stem Cells Research (2 papers), Sarcoma Diagnosis and Treatment (1 paper) and Protein Kinase Regulation and GTPase Signaling (1 paper). Ryan Vander Werff is often cited by papers focused on Pluripotent Stem Cells Research (2 papers), Sarcoma Diagnosis and Treatment (1 paper) and Protein Kinase Regulation and GTPase Signaling (1 paper). Ryan Vander Werff collaborates with scholars based in Canada, United States and Australia. Ryan Vander Werff's co-authors include Kelly M. McNagny, Michael R. Hughes, Hongxia Fu, Junjie Lu, Joseph V. Bonventre, M. Todd Valerius, Ryuji Morizane, Craig R. Brooks, Derek Peters and Anna Baccei and has published in prestigious journals such as Nature Communications, Development and Scientific Reports.

In The Last Decade

Ryan Vander Werff

7 papers receiving 752 citations

Hit Papers

Modelling kidney disease with CRISPR-mutant kidney organo... 2015 2026 2018 2022 2015 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
Ryan Vander Werff Canada 5 606 189 174 112 101 7 756
Ramila E. Gulieva United States 5 576 1.0× 201 1.1× 201 1.2× 131 1.2× 92 0.9× 7 710
Ken Hiratsuka United States 12 384 0.6× 128 0.7× 143 0.8× 47 0.4× 58 0.6× 18 523
Daniëlle G. Leuning Netherlands 8 374 0.6× 121 0.6× 124 0.7× 36 0.3× 58 0.6× 11 563
Tomoko Ohmori Japan 11 956 1.6× 415 2.2× 148 0.9× 104 0.9× 61 0.6× 16 1.0k
Shawna Tan Singapore 6 363 0.6× 80 0.4× 31 0.2× 85 0.8× 187 1.9× 7 560
Atsuhiro Taguchi Japan 15 1.5k 2.5× 716 3.8× 227 1.3× 194 1.7× 88 0.9× 19 1.6k
Shi-Jiang Lu United States 8 549 0.9× 35 0.2× 80 0.5× 48 0.4× 36 0.4× 8 835
Chris H. Chon United States 9 491 0.8× 158 0.8× 132 0.8× 71 0.6× 55 0.5× 13 862
Helen J. Rippon United Kingdom 11 469 0.8× 234 1.2× 113 0.6× 50 0.4× 30 0.3× 13 864
Ekim Z. Taşkıran Türkiye 15 329 0.5× 87 0.5× 37 0.2× 195 1.7× 84 0.8× 70 739

Countries citing papers authored by Ryan Vander Werff

Since Specialization
Citations

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

Fields of papers citing papers by Ryan Vander Werff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan Vander Werff. 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 Ryan Vander Werff. The network helps show where Ryan Vander Werff may publish in the future.

Co-authorship network of co-authors of Ryan Vander Werff

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

All Works

7 of 7 papers shown
1.
Takiguchi, Hiroto, Chen Yang, Cheng Wei Tony Yang, et al.. (2021). Macrophages with reduced expressions of classical M1 and M2 surface markers in human bronchoalveolar lavage fluid exhibit pro-inflammatory gene signatures. Scientific Reports. 11(1). 8282–8282. 32 indexed citations
2.
Takiguchi, Hiroto, Yu Hsuan Carol Yang, Cheng Wei Tony Yang, et al.. (2020). Gene Expression Signature of Human Alveolar Macrophages Recovered from Human Broncho-Alveolar Lavage. A6128–A6128. 1 indexed citations
3.
Poulin, Neal, Jared J. Barrott, Alireza Lorzadeh, et al.. (2017). Death by HDAC Inhibition in Synovial Sarcoma Cells. Molecular Cancer Therapeutics. 16(12). 2656–2667. 26 indexed citations
4.
Bagó, Juli R., Onyi Okolie, ‎Raluca Dumitru, et al.. (2017). Tumor-homing cytotoxic human induced neural stem cells for cancer therapy. Science Translational Medicine. 9(375). 76 indexed citations
5.
Phun, Jennifer, et al.. (2015). Parathyroid-hormone-related protein signaling mechanisms in lung carcinoma growth inhibition. SpringerPlus. 4(1). 268–268. 2 indexed citations
6.
Freedman, Benjamin, Craig R. Brooks, Albert Q. Lam, et al.. (2015). Modelling kidney disease with CRISPR-mutant kidney organoids derived from human pluripotent epiblast spheroids. Nature Communications. 6(1). 8715–8715. 567 indexed citations breakdown →
7.
Garside, Victoria C., Rebecca Cullum, Olivia Alder, et al.. (2015). SOX9 modulates the expression of key transcription factors required for heart valve development. Development. 142(24). 4340–50. 52 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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