Roger Patient

11.3k total citations
143 papers, 8.7k citations indexed

About

Roger Patient is a scholar working on Molecular Biology, Cell Biology and Genetics. According to data from OpenAlex, Roger Patient has authored 143 papers receiving a total of 8.7k indexed citations (citations by other indexed papers that have themselves been cited), including 125 papers in Molecular Biology, 66 papers in Cell Biology and 23 papers in Genetics. Recurrent topics in Roger Patient's work include Zebrafish Biomedical Research Applications (62 papers), Congenital heart defects research (52 papers) and Epigenetics and DNA Methylation (26 papers). Roger Patient is often cited by papers focused on Zebrafish Biomedical Research Applications (62 papers), Congenital heart defects research (52 papers) and Epigenetics and DNA Methylation (26 papers). Roger Patient collaborates with scholars based in United Kingdom, United States and Netherlands. Roger Patient's co-authors include Martin Gering, Adam Rodaway, Aldo Ciau‐Uitz, Maggie Walmsley, James D. McGhee, Nigel Holder, Matthew Loose, Feng Liu, Tessa Peterkin and Rui Monteiro and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Roger Patient

140 papers receiving 8.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roger Patient United Kingdom 51 6.9k 2.9k 1.2k 1.1k 772 143 8.7k
Naoki Takeda Japan 38 4.8k 0.7× 1.5k 0.5× 946 0.8× 936 0.9× 656 0.8× 97 7.4k
Malcolm Whitman United States 44 8.6k 1.2× 1.4k 0.5× 1.2k 1.0× 753 0.7× 543 0.7× 82 10.3k
Nathan D. Lawson United States 55 10.2k 1.5× 5.3k 1.8× 1.5k 1.2× 1.3k 1.2× 2.0k 2.6× 95 13.7k
Mary C. Beckerle United States 59 5.9k 0.8× 4.6k 1.6× 582 0.5× 684 0.6× 787 1.0× 121 10.4k
Mitchell Goldfarb United States 56 10.8k 1.6× 2.5k 0.8× 2.5k 2.1× 732 0.7× 1.1k 1.5× 98 13.9k
Bruce M. Paterson United States 33 5.9k 0.9× 905 0.3× 936 0.8× 820 0.8× 1.0k 1.3× 56 8.7k
John P. Kanki United States 38 4.2k 0.6× 3.5k 1.2× 665 0.5× 1.7k 1.6× 767 1.0× 60 7.0k
Caroline S. Hill United Kingdom 56 12.2k 1.8× 1.9k 0.6× 1.1k 0.9× 1.2k 1.1× 1.7k 2.2× 106 15.6k
Katia Manova United States 47 7.4k 1.1× 973 0.3× 1.7k 1.4× 1000 0.9× 1.6k 2.1× 79 10.7k
Yingzi Yang United States 51 7.9k 1.1× 1.9k 0.7× 2.1k 1.8× 742 0.7× 1.0k 1.3× 99 11.1k

Countries citing papers authored by Roger Patient

Since Specialization
Citations

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

Fields of papers citing papers by Roger Patient

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roger Patient

This figure shows the co-authorship network connecting the top 25 collaborators of Roger Patient. A scholar is included among the top collaborators of Roger Patient 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 Roger Patient. Roger Patient 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.
Maeda, Hiroki, Isao Kobayashi, Miki Takeuchi, et al.. (2023). LSD1 promotes the egress of hematopoietic stem and progenitor cells into the bloodstream during the endothelial-to-hematopoietic transition. Developmental Biology. 501. 92–103. 1 indexed citations
2.
Koth, Jana, Xiaonan Wang, Andrew Jefferson, et al.. (2020). Runx1 promotes scar deposition and inhibits myocardial proliferation and survival during zebrafish heart regeneration. Development. 147(8). 48 indexed citations
3.
Mahony, Christopher B., Mónika Krecsmarik, Rossella Rispoli, et al.. (2020). Deletion of a conserved Gata2 enhancer impairs haemogenic endothelium programming and adult Zebrafish haematopoiesis. Communications Biology. 3(1). 71–71. 23 indexed citations
4.
Weinberger, Michael, Filipa C. Simões, Roger Patient, Tatjana Sauka‐Spengler, & Paul R. Riley. (2020). Functional Heterogeneity within the Developing Zebrafish Epicardium. Developmental Cell. 52(5). 574–590.e6. 52 indexed citations
5.
Ciau‐Uitz, Aldo & Roger Patient. (2019). Gene Regulatory Networks Governing the Generation and Regeneration of Blood. Journal of Computational Biology. 26(7). 719–725. 8 indexed citations
6.
7.
Patient, Roger. (2014). Programming blood stem cells during Xenopus and zebrafish development. Experimental Hematology. 42(8). S3–S3. 1 indexed citations
8.
Wang, Lu, Tianhui Liu, Ya Gao, et al.. (2013). Fev regulates hematopoietic stem cell development via ERK signaling. Blood. 122(3). 367–375. 43 indexed citations
9.
Wang, Lu, Panpan Zhang, Yonglong Wei, et al.. (2011). A blood flow–dependent klf2a-NO signaling cascade is required for stabilization of hematopoietic stem cell programming in zebrafish embryos. Blood. 118(15). 4102–4110. 91 indexed citations
10.
Dee, Chris T., et al.. (2008). Sox3 regulates both neural fate and differentiation in the zebrafish ectoderm. Developmental Biology. 320(1). 289–301. 77 indexed citations
11.
Meier, N., Patrick Rodriguez, John Strouboulis, et al.. (2006). Novel binding partners of Ldb1 are required for haematopoietic development. Development. 133(24). 4913–4923. 105 indexed citations
12.
Patterson, Lucy J., Martin Gering, Craig E. Eckfeldt, et al.. (2006). The transcription factors Scl and Lmo2 act together during development of the hemangioblast in zebrafish. Blood. 109(6). 2389–2398. 115 indexed citations
13.
Patient, Roger, et al.. (2006). Genetic regulatory networks programming hematopoietic stem cells and erythroid lineage specification. Developmental Biology. 294(2). 525–540. 122 indexed citations
14.
Brewer, Alison C., Alexander Alexandrovich, Corey H. Mjaatvedt, et al.. (2005). GATA Factors Lie Upstream of Nkx 2.5 in the Transcriptional Regulatory Cascade That Effects Cardiogenesis. Stem Cells and Development. 14(4). 425–439. 39 indexed citations
15.
Gering, Martin, Yoshihiro Yamada, Terence H. Rabbitts, & Roger Patient. (2003). Lmo2 and Scl/Tal1 convert non-axial mesoderm into haemangioblasts which differentiate into endothelial cells in the absence of Gata1. Development. 130(25). 6187–6199. 145 indexed citations
16.
Rodaway, Adam & Roger Patient. (2001). Mesendoderm. Cell. 105(2). 169–172. 122 indexed citations
17.
Brown, Louise, Adam Rodaway, Thomas F. Schilling, et al.. (2000). Insights into early vasculogenesis revealed by expression of the ETS-domain transcription factor Fli-1 in wild-type and mutant zebrafish embryos. Mechanisms of Development. 90(2). 237–252. 221 indexed citations
18.
Rodaway, Adam, et al.. (1995). Expression of zebrafish GATA 3 (gta3) during gastrulation and neurulation suggests a role in the specification of cell fate. Mechanisms of Development. 51(2-3). 169–182. 87 indexed citations
19.
Leonard, Mark & Roger Patient. (1991). Evidence for Torsional Stress in Transcriptionally Activated Chromatin. Molecular and Cellular Biology. 11(12). 6128–6138. 9 indexed citations
20.
Patient, Roger, et al.. (1989). Activation mechanisms of the Xenopus beta globin gene.. UCL Discovery (University College London). 316A. 105–16. 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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