Matthew D. Beasley

615 total citations
8 papers, 461 citations indexed

About

Matthew D. Beasley is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, Matthew D. Beasley has authored 8 papers receiving a total of 461 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Oncology. Recurrent topics in Matthew D. Beasley's work include DNA Repair Mechanisms (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Genomics and Chromatin Dynamics (3 papers). Matthew D. Beasley is often cited by papers focused on DNA Repair Mechanisms (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Genomics and Chromatin Dynamics (3 papers). Matthew D. Beasley collaborates with scholars based in Australia, United States and Netherlands. Matthew D. Beasley's co-authors include Michael J. McKay, Huiling Xu, William Warren, Gijsbertus T. J. van der Horst, Sandra Verschoor, Mary Ann Handel, Amy L. Inselman, Jeroen Essers, Esther Appeldoorn and Hui-Ling Xu and has published in prestigious journals such as PLoS ONE, Cancer Cell and Genome Research.

In The Last Decade

Matthew D. Beasley

8 papers receiving 452 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew D. Beasley Australia	6	377	97	94	80	78	8	461
Avril Smith Germany	7	351 0.9×	64 0.7×	58 0.6×	71 0.9×	92 1.2×	8	409
Erwan Delbarre Norway	16	880 2.3×	87 0.9×	90 1.0×	50 0.6×	68 0.9×	22	997
Louise Newnham United Kingdom	10	345 0.9×	131 1.4×	112 1.2×	98 1.2×	146 1.9×	12	537
Yosuke Ichijima Japan	11	729 1.9×	104 1.1×	96 1.0×	63 0.8×	174 2.2×	12	823
Andrew Ha United States	8	219 0.6×	35 0.4×	144 1.5×	47 0.6×	153 2.0×	10	368
Femke A.T. de Vries Netherlands	7	346 0.9×	69 0.7×	52 0.6×	79 1.0×	141 1.8×	10	506
Cristina Gutiérrez‐Caballero Spain	10	540 1.4×	150 1.5×	323 3.4×	87 1.1×	57 0.7×	10	629
Laura Gómez-H Spain	10	433 1.1×	90 0.9×	79 0.8×	78 1.0×	126 1.6×	12	524
Yuwen Ke China	10	856 2.3×	195 2.0×	160 1.7×	64 0.8×	128 1.6×	17	926
Michel F. Guiraldelli United States	8	233 0.6×	51 0.5×	42 0.4×	52 0.7×	57 0.7×	10	295

Countries citing papers authored by Matthew D. Beasley

Since Specialization

Citations

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

Fields of papers citing papers by Matthew D. Beasley

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew D. Beasley. 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 Matthew D. Beasley. The network helps show where Matthew D. Beasley may publish in the future.

Co-authorship network of co-authors of Matthew D. Beasley

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

All Works

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8 of 8 papers shown

Liu, Jia‐Geng, Mathilde Poussin, Madhara Udawela, et al.. (2025). Mutant KRAS peptide targeted CAR-T cells engineered for cancer therapy. Cancer Cell. 43(7). 1365–1376.e5. 4 indexed citations

Sun, Yi, S. K. Gupta, Samuel E. Garfinkle, et al.. (2023). Structural principles of peptide-centric chimeric antigen receptor recognition guide therapeutic expansion. Science Immunology. 8(90). eadj5792–eadj5792. 10 indexed citations

Beasley, Matthew D., et al.. (2015). Bacterial cytoplasmic display platform Retained Display (ReD) identifies stable human germline antibody frameworks. Biotechnology Journal. 10(5). 783–789. 9 indexed citations

Winnall, Wendy R., Matthew D. Beasley, Matthew S. Parsons, Ben R. Kiefel, & Stephen J. Kent. (2014). The maturation of antibody technology for the HIV epidemic. Immunology and Cell Biology. 92(7). 570–577. 5 indexed citations

Xu, Huiling, Jordane Malaterre, Matthew D. Beasley, et al.. (2010). Rad21-Cohesin Haploinsufficiency Impedes DNA Repair and Enhances Gastrointestinal Radiosensitivity in Mice. PLoS ONE. 5(8). e12112–e12112. 82 indexed citations

Xu, Huiling, Matthew D. Beasley, William Warren, Gijsbertus T. J. van der Horst, & Michael J. McKay. (2005). Absence of Mouse REC8 Cohesin Promotes Synapsis of Sister Chromatids in Meiosis. Developmental Cell. 8(6). 949–961. 262 indexed citations

Xu, Huiling, Matthew D. Beasley, Sandra Verschoor, et al.. (2004). A new role for the mitotic RAD21/SCC1 cohesin in meiotic chromosome cohesion and segregation in the mouse. EMBO Reports. 5(4). 378–384. 65 indexed citations

Beasley, Matthew D., Hui-Ling Xu, William Warren, & R. Michael L. McKay. (2002). Conserved Disruptions in the Predicted Coiled-Coil Domains of Eukaryotic SMC Complexes: Implications for Structure and Function. Genome Research. 12(8). 1201–1209. 24 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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