Lawrence W. Chamley

11.3k total citations
28 papers, 303 citations indexed

About

Lawrence W. Chamley is a scholar working on Molecular Biology, Obstetrics and Gynecology and Cancer Research. According to data from OpenAlex, Lawrence W. Chamley has authored 28 papers receiving a total of 303 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 11 papers in Obstetrics and Gynecology and 9 papers in Cancer Research. Recurrent topics in Lawrence W. Chamley's work include Extracellular vesicles in disease (19 papers), Pregnancy and preeclampsia studies (11 papers) and MicroRNA in disease regulation (8 papers). Lawrence W. Chamley is often cited by papers focused on Extracellular vesicles in disease (19 papers), Pregnancy and preeclampsia studies (11 papers) and MicroRNA in disease regulation (8 papers). Lawrence W. Chamley collaborates with scholars based in New Zealand, United States and China. Lawrence W. Chamley's co-authors include Mancy Tong, Colin L. Hisey, Cherie Blenkiron, Neil G. R. Broderick, Wei Xu, Miguel Martínez-Calderón, Vikki M. Abrahams, Zimei Wu, Euphemia Leung and Katie Groom and has published in prestigious journals such as SHILAP Revista de lepidopterología, Analytical Chemistry and ACS Applied Materials & Interfaces.

In The Last Decade

Lawrence W. Chamley

26 papers receiving 302 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lawrence W. Chamley New Zealand 12 178 84 64 62 59 28 303
Huifang Huang China 10 151 0.8× 22 0.3× 57 0.9× 72 1.2× 57 1.0× 39 362
Guangxu Cao China 11 117 0.7× 11 0.1× 63 1.0× 23 0.4× 35 0.6× 20 278
Yixin Liao China 11 96 0.5× 76 0.9× 18 0.3× 123 2.0× 53 0.9× 33 372
Rachel R. Mizenko United States 8 348 2.0× 5 0.1× 119 1.9× 35 0.6× 114 1.9× 11 406
Hanna J. Koster United States 6 253 1.4× 5 0.1× 71 1.1× 15 0.2× 115 1.9× 8 326
Ziyang Tan China 10 159 0.9× 5 0.1× 21 0.3× 90 1.5× 128 2.2× 20 446
Qianying Zhao United States 13 134 0.8× 55 0.7× 29 0.5× 26 0.4× 40 0.7× 38 456
Shane Ford United States 5 290 1.6× 22 0.3× 145 2.3× 32 0.5× 68 1.2× 6 402
Anna Drożdż Poland 9 250 1.4× 5 0.1× 121 1.9× 50 0.8× 45 0.8× 14 344
Wilna Oosthuyzen United Kingdom 7 536 3.0× 19 0.2× 293 4.6× 28 0.5× 149 2.5× 8 619

Countries citing papers authored by Lawrence W. Chamley

Since Specialization
Citations

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

Fields of papers citing papers by Lawrence W. Chamley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lawrence W. Chamley. 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 Lawrence W. Chamley. The network helps show where Lawrence W. Chamley may publish in the future.

Co-authorship network of co-authors of Lawrence W. Chamley

This figure shows the co-authorship network connecting the top 25 collaborators of Lawrence W. Chamley. A scholar is included among the top collaborators of Lawrence W. Chamley 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 Lawrence W. Chamley. Lawrence W. Chamley 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
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Martínez-Calderón, Miguel, Xia Ning, Eduardo Reátegui, et al.. (2024). Deep autoencoder as an interpretable tool for Raman spectroscopy investigation of chemical and extracellular vesicle mixtures. Biomedical Optics Express. 15(7). 4220–4220. 8 indexed citations
4.
Leung, Euphemia, et al.. (2024). Comparing extracellular vesicles from four different cell origins for intracellular drug delivery to pancreatic cancer cells: Small or large vesicles?. Journal of Drug Delivery Science and Technology. 93. 105416–105416. 10 indexed citations
5.
Kang, Matthew, Cherie Blenkiron, & Lawrence W. Chamley. (2023). The biodistribution of placental and fetal extracellular vesicles during pregnancy following placentation. Clinical Science. 137(5). 385–399. 8 indexed citations
6.
Lau, Sandy, Alireza Akbarinejad, Lawrence W. Chamley, et al.. (2023). Electrochemical Approach for Specific Capture and Rapid Release of Nanoscale Placental Extracellular Vesicles Using Aptamer-Modified Conducting Terpolymer-Coated Carbon Cloth. ACS Applied Nano Materials. 6(5). 3981–3989. 4 indexed citations
7.
Leung, Euphemia, et al.. (2023). Functionalisation of extracellular vesicles with cyclic-RGDyC potentially for glioblastoma targeted intracellular drug delivery. Biomaterials Advances. 149. 213388–213388. 23 indexed citations
8.
Groom, Katie, et al.. (2023). Isolation and Maintenance in Culture of Primary Human Trophoblast from Term Placentae. Methods in molecular biology. 2728. 3–12. 2 indexed citations
9.
Chen, Xinyue, et al.. (2023). A pilot in vivo study: potential ovarian cancer therapeutic by placental extracellular vesicles. Bioscience Reports. 43(8). 3 indexed citations
10.
Kang, Matthew, et al.. (2023). Placental Extracellular Vesicles Can Be Loaded with Plasmid DNA. Molecular Pharmaceutics. 20(4). 1898–1913. 14 indexed citations
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Martínez-Calderón, Miguel, Claude Aguergaray, Wei Xu, et al.. (2022). Classification of Preeclamptic Placental Extracellular Vesicles Using Femtosecond Laser Fabricated Nanoplasmonic Sensors. ACS Sensors. 7(6). 1698–1711. 16 indexed citations
13.
Hisey, Colin L., Guangyu Guo, Vanessa Chang, et al.. (2022). Investigating the consistency of extracellular vesicle production from breast cancer subtypes using CELLine adherent bioreactors. SHILAP Revista de lepidopterología. 1(9). e60–e60. 12 indexed citations
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Martínez-Calderón, Miguel, et al.. (2022). Cascaded Deep Convolutional Neural Networks as Improved Methods of Preprocessing Raman Spectroscopy Data. Analytical Chemistry. 94(37). 12907–12918. 46 indexed citations
15.
Groom, Katie, et al.. (2021). A simple method to isolate term trophoblasts and maintain them in extended culture. Placenta. 108. 1–10. 15 indexed citations
16.
Lau, Sandy, et al.. (2021). Comparison of methods for separating fluorescently labelled placental extracellular vesicles from free stain. Placenta. 109. 1–3. 4 indexed citations
17.
Hisey, Colin L., Cherie Blenkiron, Lawrence W. Chamley, et al.. (2021). Space curvature-inspired nanoplasmonic sensor for breast cancer extracellular vesicle fingerprinting and machine learning classification. Biomedical Optics Express. 12(7). 3965–3965. 14 indexed citations
18.
Blenkiron, Cherie, et al.. (2020). Growing human trophoblasts in vitro : a review of the media commonly used in trophoblast cell culture. Reproduction. 160(6). R119–R128. 12 indexed citations
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Tong, Mancy & Lawrence W. Chamley. (2017). Isolation and Characterization of Extracellular Vesicles from Ex Vivo Cultured Human Placental Explants. Methods in molecular biology. 1710. 117–129. 20 indexed citations
20.
Holland, Olivia J., et al.. (2012). Syncytial nuclear aggregates, carriers of fetal alloantigens. Journal of Reproductive Immunology. 94(1). 118–118. 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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