Peter Bayliss

2.5k total citations · 2 hit papers
17 papers, 1.9k citations indexed

About

Peter Bayliss is a scholar working on Molecular Biology, Cell Biology and Physiology. According to data from OpenAlex, Peter Bayliss has authored 17 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 4 papers in Cell Biology and 4 papers in Physiology. Recurrent topics in Peter Bayliss's work include Epigenetics and DNA Methylation (4 papers), Zebrafish Biomedical Research Applications (4 papers) and Telomeres, Telomerase, and Senescence (3 papers). Peter Bayliss is often cited by papers focused on Epigenetics and DNA Methylation (4 papers), Zebrafish Biomedical Research Applications (4 papers) and Telomeres, Telomerase, and Senescence (3 papers). Peter Bayliss collaborates with scholars based in United States, Canada and Japan. Peter Bayliss's co-authors include Thomas M. Roberts, Yang Shi, Shigeki Iwase, Johnathan R. Whetstine, Fei Lan, Joanne Chan, Luis de la Torre-Ubieta, Maite Huarte, Hank H. Qi and Azad Bonni and has published in prestigious journals such as Nature, Cell and PLoS ONE.

In The Last Decade

Peter Bayliss

16 papers receiving 1.9k citations

Hit Papers

A histone H3 lysine 27 de... 2007 2026 2013 2019 2007 2007 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Bayliss United States 14 1.6k 338 301 163 144 17 1.9k
Rebecca Spokony United States 11 1.7k 1.1× 424 1.3× 297 1.0× 121 0.7× 63 0.4× 12 2.0k
Keith A. Wharton United States 20 1.5k 1.0× 232 0.7× 270 0.9× 161 1.0× 87 0.6× 36 2.1k
Anne Harrington United States 13 1.1k 0.7× 289 0.9× 236 0.8× 112 0.7× 120 0.8× 20 1.5k
Véronique Paquis‐Flucklinger France 27 2.0k 1.3× 413 1.2× 356 1.2× 178 1.1× 175 1.2× 88 2.5k
Christophe Houbron France 16 1.4k 0.9× 299 0.9× 186 0.6× 133 0.8× 133 0.9× 24 2.0k
Tatsuo Michiue Japan 26 2.1k 1.4× 386 1.1× 441 1.5× 123 0.8× 87 0.6× 84 2.5k
Steven C. Pruitt United States 23 1.4k 0.9× 252 0.7× 190 0.6× 203 1.2× 109 0.8× 40 1.8k
Roland Dosch Germany 19 2.0k 1.3× 440 1.3× 461 1.5× 144 0.9× 82 0.6× 33 2.5k
Sabine Loewer United States 10 1.8k 1.1× 290 0.9× 401 1.3× 193 1.2× 261 1.8× 11 2.3k
Brian Gebelein United States 23 1.7k 1.1× 481 1.4× 249 0.8× 125 0.8× 51 0.4× 58 2.1k

Countries citing papers authored by Peter Bayliss

Since Specialization
Citations

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

Fields of papers citing papers by Peter Bayliss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Bayliss

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

All Works

17 of 17 papers shown
1.
Hulme, Joanne T., et al.. (2025). Abstract 2889: Multabodies: A next-generation approach for cancer immunotherapy and 4-1BB agonist therapy. Cancer Research. 85(8_Supplement_1). 2889–2889.
2.
Hallett, Robin, Ester Bonfill‐Teixidor, Raffaella Iurlaro, et al.. (2022). Therapeutic Targeting of LIF Overcomes Macrophage-mediated Immunosuppression of the Local Tumor Microenvironment. Clinical Cancer Research. 29(4). 791–804. 25 indexed citations
3.
Gallo, Eugenio, Peter Bayliss, Olga Egorova, et al.. (2020). In situ antibody phage display yields optimal inhibitors of integrin α11/β1. mAbs. 12(1). 1717265–1717265. 15 indexed citations
4.
Kishi, Shuji, Peter Bayliss, & Jun‐ichi Hanai. (2014). A prospective epigenetic paradigm between cellular senescence and epithelial-mesenchymal transition in organismal development and aging. Translational research. 165(1). 241–249. 15 indexed citations
5.
Sasaki, Tomoyuki, Shanshan Lian, Jie Qi, et al.. (2014). Aberrant Autolysosomal Regulation Is Linked to The Induction of Embryonic Senescence: Differential Roles of Beclin 1 and p53 in Vertebrate Spns1 Deficiency. PLoS Genetics. 10(6). e1004409–e1004409. 1 indexed citations
6.
Wu, Xue, Jiani C. Yin, Jeremy A. Simpson, et al.. (2012). Increased BRAF Heterodimerization Is the Common Pathogenic Mechanism for Noonan Syndrome-Associated RAF1 Mutants. Molecular and Cellular Biology. 32(19). 3872–3890. 30 indexed citations
7.
Imamura, Shintaro, Junzō Uchiyama, Eriko Koshimizu, et al.. (2008). A Non-Canonical Function of Zebrafish Telomerase Reverse Transcriptase Is Required for Developmental Hematopoiesis. PLoS ONE. 3(10). e3364–e3364. 46 indexed citations
8.
Kishi, Shuji, Peter Bayliss, Junzō Uchiyama, et al.. (2008). The Identification of Zebrafish Mutants Showing Alterations in Senescence-Associated Biomarkers. PLoS Genetics. 4(8). e1000152–e1000152. 125 indexed citations
9.
Tsai, Sang‐Bing, Valter Tucci, Junzō Uchiyama, et al.. (2007). Differential effects of genotoxic stress on both concurrent body growth and gradual senescence in the adult zebrafish. Aging Cell. 6(2). 209–224. 66 indexed citations
10.
Lan, Fei, Peter Bayliss, John L. Rinn, et al.. (2007). A histone H3 lysine 27 demethylase regulates animal posterior development. Nature. 449(7163). 689–694. 621 indexed citations breakdown →
11.
Iwase, Shigeki, Fei Lan, Peter Bayliss, et al.. (2007). The X-Linked Mental Retardation Gene SMCX/JARID1C Defines a Family of Histone H3 Lysine 4 Demethylases. Cell. 128(6). 1077–1088. 529 indexed citations breakdown →
12.
Ho, Diana M., Joanne Chan, Peter Bayliss, & Malcolm Whitman. (2006). Inhibitor-resistant type I receptors reveal specific requirements for TGF-β signaling in vivo. Developmental Biology. 295(2). 730–742. 42 indexed citations
13.
Bayliss, Peter, Sandrine Aegerter, Douglas B. Cowan, et al.. (2006). Chemical modulation of receptor signaling inhibits regenerative angiogenesis in adult zebrafish. Nature Chemical Biology. 2(5). 265–273. 105 indexed citations
14.
Montero, Juan A., et al.. (2003). Phosphoinositide 3-Kinase Is Required for Process Outgrowth and Cell Polarization of Gastrulating Mesendodermal Cells. Current Biology. 13(15). 1279–1289. 103 indexed citations
15.
Chan, Joanne, Peter Bayliss, Jeanette M. Wood, & Thomas M. Roberts. (2002). Dissection of angiogenic signaling in zebrafish using a chemical genetic approach. Cancer Cell. 1(3). 257–267. 156 indexed citations
16.
Bonetta, Dario, et al.. (2000). Farnesylation is involved in meristem organization in Arabidopsis. Planta. 211(2). 182–190. 44 indexed citations
17.
Kaye, Gerry, Peter Bayliss, Philip J. Lowry, Paul Drury, & A. John Camm. (1992). Effect of induced supraventricular tachycardias on changes in urine output and plasma hormone levels in man. Clinical Science. 82(1). 33–37. 3 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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