Ryan M. Genga

4.6k total citations · 2 hit papers
18 papers, 3.4k citations indexed

About

Ryan M. Genga is a scholar working on Molecular Biology, Hematology and Genetics. According to data from OpenAlex, Ryan M. Genga has authored 18 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 6 papers in Hematology and 2 papers in Genetics. Recurrent topics in Ryan M. Genga's work include Pluripotent Stem Cells Research (6 papers), Blood Coagulation and Thrombosis Mechanisms (6 papers) and Hemophilia Treatment and Research (6 papers). Ryan M. Genga is often cited by papers focused on Pluripotent Stem Cells Research (6 papers), Blood Coagulation and Thrombosis Mechanisms (6 papers) and Hemophilia Treatment and Research (6 papers). Ryan M. Genga collaborates with scholars based in United States, Germany and Austria. Ryan M. Genga's co-authors include Francis Ka-Ming Chan, Tathagat Dutta Ray, Sreerupa Challa, Melissa Guildford, David Moquin, René Maehr, Nicola A. Kearns, Manuel Garber, Hannah Pham and Noah J. Silverstein and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Blood.

In The Last Decade

Ryan M. Genga

18 papers receiving 3.4k citations

Hit Papers

Phosphorylation-Driven Assembly of the RIP1-RIP3 Complex ... 2009 2026 2014 2020 2009 2015 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ryan M. Genga United States 13 2.7k 944 432 333 315 18 3.4k
Jing Zhao United States 31 2.3k 0.9× 645 0.7× 454 1.1× 315 0.9× 312 1.0× 107 3.4k
Olivier Donzé Switzerland 25 2.3k 0.8× 979 1.0× 289 0.7× 236 0.7× 308 1.0× 35 3.5k
Suraj Peri United States 30 2.0k 0.7× 628 0.7× 541 1.3× 383 1.2× 419 1.3× 63 3.2k
Li-Yun Ding Taiwan 12 3.0k 1.1× 1.1k 1.1× 288 0.7× 463 1.4× 861 2.7× 13 4.1k
Kaoru Tominaga Japan 24 2.6k 0.9× 653 0.7× 299 0.7× 338 1.0× 470 1.5× 74 3.5k
Diego Miranda‐Saavedra United Kingdom 28 1.8k 0.7× 582 0.6× 348 0.8× 175 0.5× 401 1.3× 43 2.8k
Sandra S. Zinkel United States 20 2.2k 0.8× 424 0.4× 386 0.9× 272 0.8× 441 1.4× 34 2.8k
Barbara Majello Italy 32 2.7k 1.0× 403 0.4× 245 0.6× 408 1.2× 557 1.8× 77 3.3k
Sigrid Cornelis Belgium 17 1.4k 0.5× 894 0.9× 529 1.2× 277 0.8× 409 1.3× 25 2.6k
Apurva Sarin India 31 1.6k 0.6× 1.4k 1.4× 371 0.9× 318 1.0× 378 1.2× 61 3.0k

Countries citing papers authored by Ryan M. Genga

Since Specialization
Citations

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

Fields of papers citing papers by Ryan M. Genga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ryan M. Genga

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

All Works

18 of 18 papers shown
1.
Kearns, Nicola A., Ryan M. Genga, Krishna Mohan Parsi, et al.. (2023). Generation and molecular characterization of human pluripotent stem cell-derived pharyngeal foregut endoderm. Developmental Cell. 58(18). 1801–1818.e15. 3 indexed citations
2.
Oksuz, Betül Akgöl, Liyan Yang, Sameer Abraham, et al.. (2021). Systematic evaluation of chromosome conformation capture assays. Nature Methods. 18(9). 1046–1055. 117 indexed citations
3.
Fischer, David S., Eric Kernfeld, Ryan M. Genga, et al.. (2019). Inferring population dynamics from single-cell RNA-sequencing time series data. Nature Biotechnology. 37(4). 461–468. 77 indexed citations
4.
Genga, Ryan M., et al.. (2019). Single-Cell RNA-Sequencing-Based CRISPRi Screening Resolves Molecular Drivers of Early Human Endoderm Development. Cell Reports. 27(3). 708–718.e10. 63 indexed citations
5.
Min, So Yun, Anand Desai, Zinger Yang, et al.. (2019). Diverse repertoire of human adipocyte subtypes develops from transcriptionally distinct mesenchymal progenitor cells. Proceedings of the National Academy of Sciences. 116(36). 17970–17979. 100 indexed citations
6.
Kernfeld, Eric, et al.. (2018). A Single-Cell Transcriptomic Atlas of Thymus Organogenesis Resolves Cell Types and Developmental Maturation. Immunity. 48(6). 1258–1270.e6. 128 indexed citations
7.
Kearns, Nicola A., Hannah Pham, Barbara Tabak, et al.. (2015). Functional annotation of native enhancers with a Cas9–histone demethylase fusion. Nature Methods. 12(5). 401–403. 504 indexed citations breakdown →
8.
Genga, Ryan M., Nicola A. Kearns, & René Maehr. (2015). Controlling transcription in human pluripotent stem cells using CRISPR-effectors. Methods. 101. 36–42. 17 indexed citations
9.
Deveau, Laura M., et al.. (2014). Allosteric inhibition of a stem cell RNA-binding protein by an intermediary metabolite. eLife. 3. 71 indexed citations
10.
Kearns, Nicola A., Ryan M. Genga, Michael J. Ziller, et al.. (2013). Generation of organized anterior foregut epithelia from pluripotent stem cells using small molecules. Stem Cell Research. 11(3). 1003–1012. 26 indexed citations
11.
Waters, Emily K., Ryan M. Genga, Heather A. Thomson, et al.. (2013). Aptamer BAX 499 mediates inhibition of tissue factor pathway inhibitor via interaction with multiple domains of the protein. Journal of Thrombosis and Haemostasis. 11(6). 1137–1145. 37 indexed citations
12.
Kearns, Nicola A., Ryan M. Genga, Metewo Selase Enuameh, et al.. (2013). Cas9 effector-mediated regulation of transcription and differentiation in human pluripotent stem cells. Development. 141(1). 219–223. 223 indexed citations
13.
Waters, Emily K., Ryan M. Genga, M. C. Schwartz, et al.. (2011). Aptamer ARC19499 mediates a procoagulant hemostatic effect by inhibiting tissue factor pathway inhibitor. Blood. 117(20). 5514–5522. 110 indexed citations
14.
Waters, Emily K., Ryan M. Genga, Heather A. Thomson, et al.. (2011). Investigation Into the Mechanism of Action and Binding Site of BAX 499, An Aptamer Against Tissue Factor Pathway Inhibitor. Blood. 118(21). 1214–1214. 1 indexed citations
15.
McGinness, Kathleen E., Emily K. Waters, Ryan M. Genga, et al.. (2010). TFPI Antagonist Aptamer ARC19499 Is a Procoagulant In Vitro and In Vivo.. Blood. 116(21). 1134–1134. 3 indexed citations
16.
Schwartz, M. C., Kathleen E. McGinness, Ryan M. Genga, et al.. (2010). Discovery and Characterization of An Anti-APC Aptamer for Use In Hemophilia. Blood. 116(21). 2222–2222. 2 indexed citations
17.
Challa, Sreerupa, David Moquin, Ryan M. Genga, et al.. (2009). Phosphorylation-Driven Assembly of the RIP1-RIP3 Complex Regulates Programmed Necrosis and Virus-Induced Inflammation. Cell. 137(6). 1112–1123. 1915 indexed citations breakdown →
18.
Waters, Emily K., Jeffrey C. Kurz, Ryan M. Genga, et al.. (2009). An Aptamer Antagonist of Tissue Factor Pathway Inhibitor Improves Coagulation in Hemophilia A and FVIII Antibody-Treated Plasma.. Blood. 114(22). 544–544. 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026