Marshall S. Padilla

1.5k total citations · 4 hit papers
27 papers, 931 citations indexed

About

Marshall S. Padilla is a scholar working on Molecular Biology, Oncology and Organic Chemistry. According to data from OpenAlex, Marshall S. Padilla has authored 27 papers receiving a total of 931 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 5 papers in Oncology and 3 papers in Organic Chemistry. Recurrent topics in Marshall S. Padilla's work include RNA Interference and Gene Delivery (18 papers), Advanced biosensing and bioanalysis techniques (10 papers) and Lipid Membrane Structure and Behavior (6 papers). Marshall S. Padilla is often cited by papers focused on RNA Interference and Gene Delivery (18 papers), Advanced biosensing and bioanalysis techniques (10 papers) and Lipid Membrane Structure and Behavior (6 papers). Marshall S. Padilla collaborates with scholars based in United States, China and Croatia. Marshall S. Padilla's co-authors include Michael J. Mitchell, Sarah J. Shepherd, Kelsey L. Swingle, Kaitlin Mrksich, Drew Weissman, Karin Wang, Mohamad‐Gabriel Alameh, Xuexiang Han, Ajay S. Thatte and Margaret M. Billingsley and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Advanced Materials.

In The Last Decade

Marshall S. Padilla

25 papers receiving 923 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Nanoparticle protein corona: from structure and function to therapeutic targeting

2023 147 citations Marshall S. Padilla, Kelsey L. Swingle et al. Lab on a Chip profile →
Rational Design of Bisphosphonate Lipid-like Materials for mRNA Delivery to the Bone Microenvironment

2022 124 citations Lulu Xue, Ningqiang Gong et al. Journal of the American Chemical Society profile →
Ionizable Lipid Nanoparticles for In Vivo mRNA Delivery to the Placenta during Pregnancy

2023 101 citations Kelsey L. Swingle, Hannah C. Safford et al. Journal of the American Chemical Society profile →
Throughput-scalable manufacturing of SARS-CoV-2 mRNA lipid nanoparticle vaccines

2023 68 citations Sarah J. Shepherd, Xuexiang Han et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Marshall S. Padilla United States	16	616	152	151	145	106	27	931
Shan Guan China	19	796 1.3×	134 0.9×	137 0.9×	156 1.1×	149 1.4×	51	1.2k
Pedro Pires Goulart Guimarães Brazil	17	516 0.8×	250 1.6×	243 1.6×	145 1.0×	92 0.9×	51	1.0k
Kamila Butowska Poland	10	614 1.0×	118 0.8×	111 0.7×	154 1.1×	52 0.5×	14	825
Jilian R. Melamed United States	14	638 1.0×	175 1.2×	155 1.0×	121 0.8×	60 0.6×	22	884
Yonger Xue United States	15	573 0.9×	235 1.5×	167 1.1×	250 1.7×	137 1.3×	25	954
Ladan Parhamifar Denmark	20	612 1.0×	206 1.4×	221 1.5×	146 1.0×	140 1.3×	31	1.0k
Hidefumi Mukai Japan	17	503 0.8×	172 1.1×	121 0.8×	53 0.4×	71 0.7×	55	819
Venkata R. Krishnamurthy United States	13	551 0.9×	178 1.2×	165 1.1×	113 0.8×	44 0.4×	16	918
Bing‐Mae Chen Taiwan	15	510 0.8×	180 1.2×	248 1.6×	270 1.9×	182 1.7×	25	1.1k
Shabnum Patel United States	14	455 0.7×	227 1.5×	251 1.7×	249 1.7×	273 2.6×	27	1.1k

Countries citing papers authored by Marshall S. Padilla

Since Specialization

Citations

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

Fields of papers citing papers by Marshall S. Padilla

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marshall S. Padilla. 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 Marshall S. Padilla. The network helps show where Marshall S. Padilla may publish in the future.

Co-authorship network of co-authors of Marshall S. Padilla

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

All Works

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20 of 20 papers shown

Padilla, Marshall S., Sarah J. Shepherd, Martin Kurnik, et al.. (2025). Elucidating lipid nanoparticle properties and structure through biophysical analyses. Nature Biotechnology. 1 indexed citations

Haley, Rebecca M., Marshall S. Padilla, Rakan El‐Mayta, et al.. (2025). Lipid Nanoparticles for In Vivo Lung Delivery of CRISPR-Cas9 Ribonucleoproteins Allow Gene Editing of Clinical Targets. ACS Nano. 19(14). 13790–13804. 6 indexed citations

Shepherd, Sarah J., Rakan El‐Mayta, Thomas F. Anderson, et al.. (2025). Automated and Parallelized Microfluidic Generation of Large and Precisely Defined Lipid Nanoparticle Libraries. ACS Nano. 20(1). 772–789.

Joseph, Ryann A., et al.. (2025). Cas9 Protein Outperforms mRNA in Lipid Nanoparticle-Mediated CFTR Repair. Nano Letters. 25(39). 14348–14355. 1 indexed citations

Geisler, Hannah C., et al.. (2024). EGFR-targeted ionizable lipid nanoparticles enhance in vivo mRNA delivery to the placenta. Journal of Controlled Release. 371. 455–469. 35 indexed citations

Han, Xuexiang, Mohamad‐Gabriel Alameh, Ningqiang Gong, et al.. (2024). Fast and facile synthesis of amidine-incorporated degradable lipids for versatile mRNA delivery in vivo. Nature Chemistry. 16(10). 1687–1697. 44 indexed citations

Mrksich, Kaitlin, Marshall S. Padilla, & Michael J. Mitchell. (2024). Breaking the final barrier: Evolution of cationic and ionizable lipid structure in lipid nanoparticles to escape the endosome. Advanced Drug Delivery Reviews. 214. 115446–115446. 38 indexed citations

Han, Emily L., Marshall S. Padilla, Rohan Palanki, et al.. (2024). Predictive High-Throughput Platform for Dual Screening of mRNA Lipid Nanoparticle Blood–Brain Barrier Transfection and Crossing. Nano Letters. 24(5). 1477–1486. 42 indexed citations

Han, Emily L., Kelsey L. Swingle, Alex G. Hamilton, et al.. (2024). Peptide-Functionalized Lipid Nanoparticles for Targeted Systemic mRNA Delivery to the Brain. Nano Letters. 25(2). 800–810. 41 indexed citations

10.

Padilla, Marshall S., et al.. (2024). Lipid nanoparticle‐mediated RNA delivery for immune cell modulation. European Journal of Immunology. 54(12). e2451008–e2451008. 8 indexed citations

11.

Mukalel, Alvin J., Alex G. Hamilton, Margaret M. Billingsley, et al.. (2024). Oxidized mRNA Lipid Nanoparticles for In Situ Chimeric Antigen Receptor Monocyte Engineering. Advanced Functional Materials. 34(27). 26 indexed citations

12.

Prazeres, Pedro Henrique Dias Moura, Pedro Augusto Carvalho Costa, Marshall S. Padilla, et al.. (2023). Delivery of Plasmid DNA by Ionizable Lipid Nanoparticles to Induce CAR Expression in T Cells. International Journal of Nanomedicine. Volume 18. 5891–5904. 23 indexed citations

13.

Shepherd, Sarah J., Xuexiang Han, Alvin J. Mukalel, et al.. (2023). Throughput-scalable manufacturing of SARS-CoV-2 mRNA lipid nanoparticle vaccines. Proceedings of the National Academy of Sciences. 120(33). e2303567120–e2303567120. 68 indexed citations breakdown →

14.

Padilla, Marshall S., et al.. (2023). Nanoparticle protein corona: from structure and function to therapeutic targeting. Lab on a Chip. 23(6). 1432–1466. 147 indexed citations breakdown →

15.

Swingle, Kelsey L., Hannah C. Safford, Hannah C. Geisler, et al.. (2023). Ionizable Lipid Nanoparticles for In Vivo mRNA Delivery to the Placenta during Pregnancy. Journal of the American Chemical Society. 145(8). 4691–4706. 101 indexed citations breakdown →

16.

Haley, Rebecca M., Alexander Chan, Margaret M. Billingsley, et al.. (2023). Lipid Nanoparticle Delivery of Small Proteins for Potent In Vivo RAS Inhibition. ACS Applied Materials & Interfaces. 15(18). 21877–21892. 29 indexed citations

17.

Zhang, Hanwen, Xuexiang Han, Mohamad‐Gabriel Alameh, et al.. (2022). Rational design of anti‐inflammatory lipid nanoparticles for mRNA delivery. Journal of Biomedical Materials Research Part A. 110(5). 1101–1108. 48 indexed citations

18.

Padilla, Marshall S., et al.. (2021). Expanding the structural diversity of hydrophobic ionic liquids: physicochemical properties and toxicity of Gemini ionic liquids. Green Chemistry. 23(12). 4375–4385. 13 indexed citations

19.

Padilla, Marshall S., et al.. (2017). Investigation of copper-free alkyne/azide 1,3-dipolar cycloadditions using microwave irradiation. Bioorganic & Medicinal Chemistry Letters. 28(2). 81–84. 11 indexed citations

20.

Padilla, Marshall S. & Douglas D. Young. (2014). Photosensitive GFP mutants containing an azobenzene unnatural amino acid. Bioorganic & Medicinal Chemistry Letters. 25(3). 470–473. 12 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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