Nicole DelRosso

740 total citations
9 papers, 342 citations indexed

About

Nicole DelRosso is a scholar working on Molecular Biology, Electrical and Electronic Engineering and Cellular and Molecular Neuroscience. According to data from OpenAlex, Nicole DelRosso has authored 9 papers receiving a total of 342 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Electrical and Electronic Engineering and 1 paper in Cellular and Molecular Neuroscience. Recurrent topics in Nicole DelRosso's work include RNA and protein synthesis mechanisms (3 papers), Advanced biosensing and bioanalysis techniques (3 papers) and Genomics and Chromatin Dynamics (3 papers). Nicole DelRosso is often cited by papers focused on RNA and protein synthesis mechanisms (3 papers), Advanced biosensing and bioanalysis techniques (3 papers) and Genomics and Chromatin Dynamics (3 papers). Nicole DelRosso collaborates with scholars based in United States. Nicole DelRosso's co-authors include Xuelong Mi, Nathan D. Derr, Michael E. Reitman, Yizhi Wang, Michelle K. Cahill, Kira E. Poskanzer, Guoqiang Yu, Silvia Pittolo, Peter Suzuki and Michael C. Bassik and has published in prestigious journals such as Nature, Cell and Angewandte Chemie International Edition.

In The Last Decade

Nicole DelRosso

9 papers receiving 342 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicole DelRosso United States 6 221 85 62 32 25 9 342
Reiko Nakatomi Japan 8 283 1.3× 99 1.2× 24 0.4× 43 1.3× 30 1.2× 11 434
Ulrik Günther Germany 3 96 0.4× 86 1.0× 30 0.5× 33 1.0× 26 1.0× 5 255
Caroline Dubacq France 10 207 0.9× 88 1.0× 41 0.7× 14 0.4× 24 1.0× 17 380
Marc Dos Santos United States 11 217 1.0× 138 1.6× 36 0.6× 42 1.3× 21 0.8× 15 429
Mark A. Lobas United States 4 320 1.4× 148 1.7× 33 0.5× 11 0.3× 20 0.8× 4 422
Gabriela Pregernig United States 4 248 1.1× 44 0.5× 23 0.4× 98 3.1× 15 0.6× 4 403
Amit K. Chouhan United States 9 188 0.9× 236 2.8× 45 0.7× 27 0.8× 19 0.8× 10 403
Martin Holub Czechia 9 104 0.5× 57 0.7× 47 0.8× 24 0.8× 10 0.4× 19 344
Sachiko Tsuda Japan 11 153 0.7× 131 1.5× 27 0.4× 60 1.9× 40 1.6× 28 335
Sebastiano Curreli Italy 5 88 0.4× 90 1.1× 27 0.4× 30 0.9× 25 1.0× 7 184

Countries citing papers authored by Nicole DelRosso

Since Specialization
Citations

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

Fields of papers citing papers by Nicole DelRosso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicole DelRosso

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

All Works

9 of 9 papers shown
1.
Aditham, Arjun K., et al.. (2025). Mutations to transcription factor MAX allosterically increase DNA selectivity by altering folding and binding pathways. Nature Communications. 16(1). 636–636. 2 indexed citations
2.
DelRosso, Nicole, Josh Tycko, Peter Suzuki, et al.. (2023). Large-scale mapping and mutagenesis of human transcriptional effector domains. Nature. 616(7956). 365–372. 72 indexed citations
3.
Tycko, Josh, Nicole DelRosso, Gaelen T. Hess, et al.. (2020). High-Throughput Discovery and Characterization of Human Transcriptional Effectors. Cell. 183(7). 2020–2035.e16. 79 indexed citations
4.
Aditham, Arjun K., Craig J. Markin, Daniel A. Mokhtari, Nicole DelRosso, & Polly M. Fordyce. (2020). High-Throughput Affinity Measurements of Transcription Factor and DNA Mutations Reveal Affinity and Specificity Determinants. Cell Systems. 12(2). 112–127.e11. 21 indexed citations
5.
Fordyce, Polly M., et al.. (2020). Leveraging Microfluidics for High‐Throughput Studies of Transcription Factor/DNA Binding. The FASEB Journal. 34(S1). 1–1. 1 indexed citations
6.
Wang, Yizhi, Nicole DelRosso, Michelle K. Cahill, et al.. (2019). Accurate quantification of astrocyte and neurotransmitter fluorescence dynamics for single-cell and population-level physiology. Nature Neuroscience. 22(11). 1936–1944. 126 indexed citations
7.
DelRosso, Nicole, et al.. (2017). A Molecular Circuit Regenerator to Implement Iterative Strand Displacement Operations. Angewandte Chemie International Edition. 56(16). 4443–4446. 22 indexed citations
8.
DelRosso, Nicole & Nathan D. Derr. (2017). Exploiting molecular motors as nanomachines: the mechanisms of de novo and re-engineered cytoskeletal motors. Current Opinion in Biotechnology. 46. 20–26. 15 indexed citations
9.
DelRosso, Nicole, et al.. (2017). A Molecular Circuit Regenerator to Implement Iterative Strand Displacement Operations. Angewandte Chemie. 129(16). 4514–4517. 4 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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