Ryan M. Williams

4.8k total citations · 1 hit paper
47 papers, 3.7k citations indexed

About

Ryan M. Williams is a scholar working on Molecular Biology, Biomedical Engineering and Materials Chemistry. According to data from OpenAlex, Ryan M. Williams has authored 47 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 14 papers in Biomedical Engineering and 13 papers in Materials Chemistry. Recurrent topics in Ryan M. Williams's work include Advanced biosensing and bioanalysis techniques (17 papers), Carbon Nanotubes in Composites (9 papers) and Advanced Biosensing Techniques and Applications (6 papers). Ryan M. Williams is often cited by papers focused on Advanced biosensing and bioanalysis techniques (17 papers), Carbon Nanotubes in Composites (9 papers) and Advanced Biosensing Techniques and Applications (6 papers). Ryan M. Williams collaborates with scholars based in United States, United Kingdom and Argentina. Ryan M. Williams's co-authors include Daniel A. Heller, Celeste J. Brown, Andrew Campen, Zoran Obradović, Ethan C. Garner, K. W. Hipps, Michael D. Griswold, Pedro Romero, Charles R. Kissinger and Jeong Seok Oh and has published in prestigious journals such as SHILAP Revista de lepidopterología, Nano Letters and ACS Nano.

In The Last Decade

Ryan M. Williams

42 papers receiving 3.7k citations

Hit Papers

Intrinsically disordered protein 2001 2026 2009 2017 2001 500 1000 1.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ryan M. Williams United States 22 2.6k 1.0k 597 241 232 47 3.7k
Stanley C. Gill United States 19 5.8k 2.3× 832 0.8× 583 1.0× 228 0.9× 480 2.1× 40 7.2k
R.L. Brady United Kingdom 39 3.3k 1.3× 591 0.6× 168 0.3× 106 0.4× 334 1.4× 87 4.7k
J. B. Alexander Ross United States 33 2.5k 1.0× 555 0.5× 156 0.3× 364 1.5× 255 1.1× 127 3.9k
Satoshi Endo Japan 36 1.8k 0.7× 529 0.5× 235 0.4× 180 0.7× 284 1.2× 193 4.1k
Christopher D. Putnam United States 39 4.7k 1.8× 691 0.7× 105 0.2× 132 0.5× 374 1.6× 79 5.8k
Jan T. Rasmussen Denmark 34 2.0k 0.8× 941 0.9× 128 0.2× 1.3k 5.5× 228 1.0× 79 5.1k
Bradley L. Pentelute United States 40 4.6k 1.8× 381 0.4× 601 1.0× 261 1.1× 118 0.5× 153 6.2k
Eric W. Hewitt United Kingdom 35 2.9k 1.1× 286 0.3× 230 0.4× 130 0.5× 563 2.4× 56 5.1k
Alok K. Mitra New Zealand 32 2.5k 1.0× 253 0.2× 249 0.4× 133 0.6× 395 1.7× 164 4.2k
Alexey Kikhney Germany 18 3.8k 1.5× 1.6k 1.5× 246 0.4× 280 1.2× 457 2.0× 29 5.6k

Countries citing papers authored by Ryan M. Williams

Since Specialization
Citations

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

Fields of papers citing papers by Ryan M. Williams

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan M. Williams. 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 Ryan M. Williams. The network helps show where Ryan M. Williams may publish in the future.

Co-authorship network of co-authors of Ryan M. Williams

This figure shows the co-authorship network connecting the top 25 collaborators of Ryan M. Williams. A scholar is included among the top collaborators of Ryan M. Williams 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 Ryan M. Williams. Ryan M. Williams 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
2.
Yamaguchi, Shinobu, Chintan H. Kapadia, Taylor F. Berryhill, et al.. (2024). Rapamycin-encapsulated nanoparticle delivery in polycystic kidney disease mice. Scientific Reports. 14(1). 15140–15140. 3 indexed citations
3.
Williams, Ryan M., et al.. (2024). Single-Walled Carbon Nanotubes as Optical Transducers for Nanobiosensors In Vivo. ACS Nano. 18(52). 35164–35181. 13 indexed citations
4.
Laursen, Kristian B., Ryan M. Williams, Johannes C. van der Mijn, et al.. (2023). NDUFA4L2 reduces mitochondrial respiration resulting in defective lysosomal trafficking in clear cell renal cell carcinoma. Cancer Biology & Therapy. 24(1). 2170669–2170669. 12 indexed citations
5.
Veiras, Luciana C., Ellen A. Bernstein, Duo‐Yao Cao, et al.. (2022). Tubular IL-1β Induces Salt Sensitivity in Diabetes by Activating Renal Macrophages. Circulation Research. 131(1). 59–73. 34 indexed citations
6.
Williams, Ryan M., et al.. (2022). Optimization of ssDNA-SWCNT Ultracentrifugation via Efficacy Measurements. ECS Journal of Solid State Science and Technology. 11(10). 101009–101009. 2 indexed citations
7.
Williams, Ryan M., et al.. (2022). Formulation of Lipid-Free Polymeric Mesoscale Nanoparticles Encapsulating mRNA. Pharmaceutical Research. 39(11). 2699–2707. 3 indexed citations
8.
Williams, Ryan M., Janki Shah, Elizabeth Mercer, et al.. (2022). Kidney-Targeted Redox Scavenger Therapy Prevents Cisplatin-Induced Acute Kidney Injury. Frontiers in Pharmacology. 12. 790913–790913. 26 indexed citations
9.
Williams, Ryan M., Shi Chen, Thomas Vito Galassi, et al.. (2021). Harnessing nanotechnology to expand the toolbox of chemical biology. Nature Chemical Biology. 17(2). 129–137. 28 indexed citations
10.
Han, Sang Jun, Ryan M. Williams, Vivette D. D’Agati, et al.. (2020). Selective nanoparticle-mediated targeting of renal tubular Toll-like receptor 9 attenuates ischemic acute kidney injury. Kidney International. 98(1). 76–87. 78 indexed citations
11.
Han, Sang Jun, Ryan M. Williams, Mihwa Kim, et al.. (2020). Renal proximal tubular NEMO plays a critical role in ischemic acute kidney injury. JCI Insight. 5(19). 13 indexed citations
12.
Williams, Ryan M., Christopher L. Lee, Thomas Vito Galassi, et al.. (2018). Noninvasive ovarian cancer biomarker detection via an optical nanosensor implant. Science Advances. 4(4). eaaq1090–eaaq1090. 126 indexed citations
13.
Harvey, Jackson D., Prakrit V. Jena, Hanan Baker, et al.. (2017). A carbon nanotube reporter of microRNA hybridization events in vivo. Nature Biomedical Engineering. 1(4). 157 indexed citations
14.
Williams, Ryan M., Edgar A. Jaimes, & Daniel A. Heller. (2016). Nanomedicines for kidney diseases. Kidney International. 90(4). 740–745. 78 indexed citations
15.
Roxbury, Daniel, Prakrit V. Jena, Ryan M. Williams, et al.. (2015). Hyperspectral Microscopy of Near-Infrared Fluorescence Enables 17-Chirality Carbon Nanotube Imaging. Scientific Reports. 5(1). 14167–14167. 113 indexed citations
17.
Williams, Ryan M., et al.. (2014). Identification of an antibody fragment specific for androgen-dependent prostate cancer cells. BMC Biotechnology. 14(1). 81–81. 13 indexed citations
18.
Williams, Ryan M., et al.. (2014). In Vitro Selection of a Single-Stranded DNA Molecular Recognition Element for the Pesticide Malathion. Combinatorial Chemistry & High Throughput Screening. 17(8). 694–702. 17 indexed citations
19.
Campen, Andrew, Ryan M. Williams, Celeste J. Brown, et al.. (2008). TOP-IDP-Scale: A New Amino Acid Scale Measuring Propensity for Intrinsic Disorder. Protein and Peptide Letters. 15(9). 956–963. 325 indexed citations
20.
Dunker, A. Keith, J. David Lawson, Celeste J. Brown, et al.. (2001). Intrinsically disordered protein. Journal of Molecular Graphics and Modelling. 19(1). 26–59. 1823 indexed citations breakdown →

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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