Daniel G. Booth

1.1k total citations
19 papers, 747 citations indexed

About

Daniel G. Booth is a scholar working on Molecular Biology, Cell Biology and Plant Science. According to data from OpenAlex, Daniel G. Booth has authored 19 papers receiving a total of 747 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 11 papers in Cell Biology and 4 papers in Plant Science. Recurrent topics in Daniel G. Booth's work include Microtubule and mitosis dynamics (9 papers), Genomics and Chromatin Dynamics (9 papers) and RNA Research and Splicing (5 papers). Daniel G. Booth is often cited by papers focused on Microtubule and mitosis dynamics (9 papers), Genomics and Chromatin Dynamics (9 papers) and RNA Research and Splicing (5 papers). Daniel G. Booth collaborates with scholars based in United Kingdom, Japan and United States. Daniel G. Booth's co-authors include William C. Earnshaw, Ian A. Prior, Stephen Royle, Fiona E. Hood, Kumiko Samejima, Giulia Vargiu, Alastair Kerr, Michael I. Robson, Jose I. de las Heras and Shaun Webb and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Cell Biology.

In The Last Decade

Daniel G. Booth

18 papers receiving 744 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel G. Booth United Kingdom	11	627	294	114	68	32	19	747
Susana A. Ribeiro United Kingdom	12	795 1.3×	494 1.7×	280 2.5×	69 1.0×	30 0.9×	16	929
Carly I. Dix United Kingdom	8	449 0.7×	450 1.5×	63 0.6×	60 0.9×	19 0.6×	9	602
Yuanliang Zhai Hong Kong	14	696 1.1×	115 0.4×	45 0.4×	67 1.0×	46 1.4×	30	796
Rachel Santarella Germany	11	925 1.5×	445 1.5×	99 0.9×	91 1.3×	34 1.1×	12	1.1k
Naoka Tamura United Kingdom	9	434 0.7×	209 0.7×	51 0.4×	131 1.9×	68 2.1×	9	549
Katrin Pfleghaar Germany	7	1.4k 2.2×	314 1.1×	39 0.3×	52 0.8×	36 1.1×	7	1.5k
Aliaksandr Halavatyi Germany	10	413 0.7×	107 0.4×	24 0.2×	74 1.1×	115 3.6×	22	569
Annabelle Alves France	7	926 1.5×	207 0.7×	36 0.3×	36 0.5×	39 1.2×	7	1.0k
Naoko Yoshizawa-Sugata Japan	12	812 1.3×	239 0.8×	146 1.3×	150 2.2×	70 2.2×	20	936
Beata E. Mierzwa United States	7	517 0.8×	321 1.1×	26 0.2×	41 0.6×	54 1.7×	9	683

Countries citing papers authored by Daniel G. Booth

Since Specialization

Citations

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

Fields of papers citing papers by Daniel G. Booth

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel G. Booth. 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 Daniel G. Booth. The network helps show where Daniel G. Booth may publish in the future.

Co-authorship network of co-authors of Daniel G. Booth

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

All Works

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19 of 19 papers shown

Kad, Neil M., et al.. (2025). The mitotic chromosome periphery modulates chromosome mechanics. Nature Communications. 16(1). 6399–6399.

Cisneros-Soberanis, Fernanda, Alison J. Beckett, Samuel Corless, et al.. (2024). Near millimolar concentration of nucleosomes in mitotic chromosomes from late prometaphase into anaphase. The Journal of Cell Biology. 223(11). 4 indexed citations

Malavasi, Elise L.V., Aniket Ghosh, Daniel G. Booth, et al.. (2021). Dynamic early clusters of nodal proteins contribute to node of Ranvier assembly during myelination of peripheral neurons. eLife. 10. 6 indexed citations

Booth, Daniel G., et al.. (2021). Characterizing the molecular etiology of arthrogryposis multiplex congenita in patients with LGI4 mutations. Glia. 69(11). 2605–2617. 1 indexed citations

Booth, Daniel G., Alison J. Beckett, Ian A. Prior, & Dies Meijer. (2019). SuperCLEM: an accessible correlative light and electron microscopy approach for investigation of neurons and glia in vitro. Biology Open. 8(5). 7 indexed citations

Booth, Daniel G., et al.. (2019). In vitro BioID: mapping the CENP-A microenvironment with high temporal and spatial resolution. Molecular Biology of the Cell. 30(11). 1314–1325. 17 indexed citations

Samejima, Kumiko, et al.. (2018). First person – Kumiko Samejima and Daniel Booth. Journal of Cell Science. 131(4). 1 indexed citations

Samejima, Kumiko, Daniel G. Booth, Hiromi Ogawa, et al.. (2018). Functional analysis after rapid degradation of condensins and 3D-EM reveals chromatin volume is uncoupled from chromosome architecture in mitosis. Journal of Cell Science. 131(4). 44 indexed citations

Booth, Daniel G. & William C. Earnshaw. (2017). Ki-67 and the Chromosome Periphery Compartment in Mitosis. Trends in Cell Biology. 27(12). 906–916. 54 indexed citations

10.

Vargiu, Giulia, et al.. (2017). Stepwise unfolding supports a subunit model for vertebrate kinetochores. Proceedings of the National Academy of Sciences. 114(12). 3133–3138. 14 indexed citations

11.

Booth, Daniel G., Alison J. Beckett, Òscar Molina, et al.. (2016). 3D-CLEM Reveals that a Major Portion of Mitotic Chromosomes Is Not Chromatin. Molecular Cell. 64(4). 790–802. 85 indexed citations

12.

Robson, Michael I., Jose I. de las Heras, Rafal Czapiewski, et al.. (2016). Tissue-Specific Gene Repositioning by Muscle Nuclear Membrane Proteins Enhances Repression of Critical Developmental Genes during Myogenesis. Molecular Cell. 62(6). 834–847. 133 indexed citations

13.

Booth, Daniel G., Giulia Vargiu, Shinya Ohta, et al.. (2016). Auxin/AID versus conventional knockouts: distinguishing the roles of CENP-T/W in mitotic kinetochore assembly and stability. Open Biology. 6(1). 150230–150230. 19 indexed citations

14.

Gutiérrez‐Caballero, Cristina, et al.. (2015). The mesh is a network of microtubule connectors that stabilizes individual kinetochore fibers of the mitotic spindle. eLife. 4. 38 indexed citations

15.

Booth, Daniel G., Masatoshi Takagi, Giulia Vargiu, et al.. (2014). Ki-67 is a PP1-interacting protein that organises the mitotic chromosome periphery. Edinburgh Research Explorer (University of Edinburgh). 1 indexed citations

16.

Booth, Daniel G., Masatoshi Takagi, Luis Sánchez‐Pulido, et al.. (2014). Ki-67 is a PP1-interacting protein that organises the mitotic chromosome periphery. eLife. 3. e01641–e01641. 155 indexed citations

17.

Booth, Daniel G., et al.. (2013). Studying Kinetochore-Fiber Ultrastructure Using Correlative Light-Electron Microscopy. Methods in cell biology. 115. 327–342. 10 indexed citations

18.

Booth, Daniel G., Fiona E. Hood, Ian A. Prior, & Stephen Royle. (2011). A TACC3/ch‐TOG/clathrin complex stabilises kinetochore fibres by inter‐microtubule bridging. The EMBO Journal. 30(5). 906–919. 124 indexed citations

19.

Booth, Daniel G., et al.. (2011). Aurora A kinase activity is required for localization of TACC3/ch-TOG/clathrin inter-microtubule bridges. Communicative & Integrative Biology. 4(4). 409–412. 34 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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