David Ross

6.2k total citations · 2 hit papers
96 papers, 4.7k citations indexed

About

David Ross is a scholar working on Biomedical Engineering, Molecular Biology and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, David Ross has authored 96 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Biomedical Engineering, 18 papers in Molecular Biology and 12 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in David Ross's work include Microfluidic and Capillary Electrophoresis Applications (40 papers), Microfluidic and Bio-sensing Technologies (32 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (12 papers). David Ross is often cited by papers focused on Microfluidic and Capillary Electrophoresis Applications (40 papers), Microfluidic and Bio-sensing Technologies (32 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (12 papers). David Ross collaborates with scholars based in United States, France and Egypt. David Ross's co-authors include Laurie E. Locascio, R.M. Bustin, Michael Gaitan, Timothy J. Johnson, Daniel Bonn, Jonathan G. Shackman, Elizabeth A. Strychalski, Christopher A. Voigt, P. Taborek and J. E. Rutledge and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

David Ross

94 papers receiving 4.6k citations

Hit Papers

Genetic circuit design automation 2007 2026 2013 2019 2016 2007 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Ross United States 31 2.5k 990 709 520 460 96 4.7k
Hans‐Joachim Krause Germany 31 1.1k 0.4× 557 0.6× 781 1.1× 376 0.7× 418 0.9× 224 4.0k
Kenji Yasuoka Japan 44 1.1k 0.4× 806 0.8× 656 0.9× 459 0.9× 1.4k 3.1× 244 5.9k
Yitzhak Rabin Israel 37 2.9k 1.2× 1.5k 1.5× 811 1.1× 208 0.4× 1.4k 3.0× 164 6.1k
Ralf Blossey France 29 1.3k 0.5× 707 0.7× 1.1k 1.5× 647 1.2× 1.2k 2.6× 135 4.9k
Fernando Bresme United Kingdom 39 1.4k 0.5× 422 0.4× 384 0.5× 384 0.7× 1.7k 3.7× 161 4.9k
D.J. Evans Australia 25 1.2k 0.5× 811 0.8× 376 0.5× 276 0.5× 1.7k 3.8× 59 4.6k
Ronald E. Rosensweig United States 32 4.0k 1.6× 1.3k 1.3× 584 0.8× 152 0.3× 1.1k 2.4× 66 5.8k
B. D. Todd Australia 35 2.9k 1.2× 253 0.3× 641 0.9× 264 0.5× 2.4k 5.3× 141 5.1k
D. R. M. Williams Australia 34 830 0.3× 494 0.5× 344 0.5× 208 0.4× 1.4k 3.0× 135 4.1k
Peter J. Daivis Australia 32 2.3k 0.9× 237 0.2× 291 0.4× 213 0.4× 1.8k 3.8× 112 3.8k

Countries citing papers authored by David Ross

Since Specialization
Citations

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

Fields of papers citing papers by David Ross

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Ross. 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 David Ross. The network helps show where David Ross may publish in the future.

Co-authorship network of co-authors of David Ross

This figure shows the co-authorship network connecting the top 25 collaborators of David Ross. A scholar is included among the top collaborators of David Ross 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 David Ross. David Ross 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
1.
d’Oelsnitz, Simon, et al.. (2024). Ligify: Automated Genome Mining for Ligand-Inducible Transcription Factors. ACS Synthetic Biology. 13(8). 2577–2586. 7 indexed citations
2.
Alperovich, Nina, Benjamin Scott, & David Ross. (2023). Automation protocol for high-efficiency and high-quality genomic DNA extraction from Saccharomyces cerevisiae. PLoS ONE. 18(10). e0292401–e0292401. 2 indexed citations
3.
Tonner, Peter D., Abe Pressman, Nathan D. Olson, et al.. (2023). Precision engineering of biological function with large-scale measurements and machine learning. PLoS ONE. 18(3). e0283548–e0283548. 2 indexed citations
4.
Rammohan, Jayan, et al.. (2022). Single-cell measurement quality in bits. PLoS ONE. 17(8). e0269272–e0269272.
5.
Ross, David, et al.. (2022). Method for reproducible automated bacterial cell culture and measurement. PubMed. 7(1). ysac013–ysac013. 5 indexed citations
6.
Tonner, Peter D., Abe Pressman, & David Ross. (2022). Interpretable modeling of genotype–phenotype landscapes with state-of-the-art predictive power. Proceedings of the National Academy of Sciences. 119(26). e2114021119–e2114021119. 21 indexed citations
7.
Alperovich, Nina, et al.. (2022). Effects of DNA template preparation on variability in cell-free protein production. PubMed. 7(1). ysac015–ysac015. 6 indexed citations
8.
Alperovich, Nina, et al.. (2022). Best Practices for DNA Template Preparation Toward Improved Reproducibility in Cell-Free Protein Production. Methods in molecular biology. 2433. 3–50. 4 indexed citations
9.
Tonner, Peter D., Abe Pressman, Nathan D. Olson, et al.. (2021). The genotype‐phenotype landscape of an allosteric protein. Molecular Systems Biology. 17(3). e10179–e10179. 39 indexed citations
10.
Shao, Bin, Jayan Rammohan, Daniel A. Anderson, et al.. (2021). Single-cell measurement of plasmid copy number and promoter activity. Nature Communications. 12(1). 1475–1475. 56 indexed citations
11.
Rammohan, Jayan, Steven P. Lund, Nina Alperovich, et al.. (2021). Comparison of bias and resolvability in single-cell and single-transcript methods. Communications Biology. 4(1). 659–659. 4 indexed citations
12.
Ross, David. (2021). Automated analysis of bacterial flow cytometry data with FlowGateNIST. PLoS ONE. 16(8). e0250753–e0250753. 7 indexed citations
13.
Ross, David, et al.. (2020). Sparse estimation of mutual information landscapes quantifies information transmission through cellular biochemical reaction networks. Communications Biology. 3(1). 203–203. 12 indexed citations
14.
Ross, David, Elizabeth A. Strychalski, Christopher Jarzynski, & Samuel M. Stavis. (2018). Equilibrium free energies from non-equilibrium trajectories with relaxation fluctuation spectroscopy. Nature Physics. 14(8). 842–847. 10 indexed citations
15.
Ross, David, Jonathan G. Shackman, Jason G. Kralj, & Javier Atencia. (2010). 2D separations on a 1D chip: gradient elution moving boundary electrophoresis—chiral capillary zone electrophoresis. Lab on a Chip. 10(22). 3139–3139. 9 indexed citations
16.
Ross, David, et al.. (2010). Determination of inorganic ions in mineral water by gradient elution moving boundary electrophoresis. Electrophoresis. 31(20). 3466–3474. 20 indexed citations
17.
Danger, Grégoire & David Ross. (2008). Development of a temperature gradient focusing method for in situ extraterrestrial biomarker analysis. Electrophoresis. 29(15). 3107–3114. 18 indexed citations
18.
Shackman, Jonathan G. & David Ross. (2007). Counter‐flow gradient electrofocusing. Electrophoresis. 28(4). 556–571. 72 indexed citations
19.
Shackman, Jonathan G., Matthew Munson, & David Ross. (2006). Temperature gradient focusing for microchannel separations. Analytical and Bioanalytical Chemistry. 387(1). 155–158. 32 indexed citations
20.
O’Leary, Brian, et al.. (1979). Retrieval of asteroidal materials. NASA Special Publication. 428. 173–189. 16 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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