Sean M. Gross

1.0k total citations
23 papers, 315 citations indexed

About

Sean M. Gross is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Sean M. Gross has authored 23 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 4 papers in Oncology and 3 papers in Cell Biology. Recurrent topics in Sean M. Gross's work include Muscle Physiology and Disorders (5 papers), PI3K/AKT/mTOR signaling in cancer (5 papers) and Single-cell and spatial transcriptomics (4 papers). Sean M. Gross is often cited by papers focused on Muscle Physiology and Disorders (5 papers), PI3K/AKT/mTOR signaling in cancer (5 papers) and Single-cell and spatial transcriptomics (4 papers). Sean M. Gross collaborates with scholars based in United States, Canada and South Korea. Sean M. Gross's co-authors include Peter Rotwein, Laura M. Heiser, Steven L. Lehman, Mark Dane, Elmar Bucher, Hye Kyoung Sung, Young Hwan Chang, Patricia L. Mitchell, André Marette and Aaron S. Meyer and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and PLoS ONE.

In The Last Decade

Sean M. Gross

21 papers receiving 312 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sean M. Gross United States 12 215 49 37 35 29 23 315
Diana Douglas United States 6 220 1.0× 31 0.6× 42 1.1× 35 1.0× 26 0.9× 9 312
Santhosh Palani United States 9 272 1.3× 27 0.6× 37 1.0× 30 0.9× 10 0.3× 11 353
Oleksii S. Rukhlenko Ireland 12 294 1.4× 32 0.7× 50 1.4× 65 1.9× 10 0.3× 25 426
Xiao Fu United Kingdom 10 124 0.6× 15 0.3× 28 0.8× 15 0.4× 22 0.8× 28 306
Xinyuan Liu China 8 339 1.6× 18 0.4× 54 1.5× 18 0.5× 22 0.8× 13 503
Hongcheng Mai China 10 149 0.7× 74 1.5× 24 0.6× 13 0.4× 9 0.3× 21 359
Mita Patel United States 5 351 1.6× 12 0.2× 25 0.7× 27 0.8× 17 0.6× 8 514
Yubo Fan United States 6 206 1.0× 35 0.7× 35 0.9× 13 0.4× 6 0.2× 9 309
Laurent Winckers Netherlands 3 348 1.6× 12 0.2× 52 1.4× 17 0.5× 16 0.6× 4 534

Countries citing papers authored by Sean M. Gross

Since Specialization
Citations

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

Fields of papers citing papers by Sean M. Gross

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sean M. Gross

This figure shows the co-authorship network connecting the top 25 collaborators of Sean M. Gross. A scholar is included among the top collaborators of Sean M. Gross 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 Sean M. Gross. Sean M. Gross 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.
Calistri, Nicholas L., Tiera Liby, Zhi Hu, et al.. (2025). TNBC response to paclitaxel phenocopies interferon response which reveals cell cycle-associated resistance mechanisms. Scientific Reports. 15(1). 4294–4294. 1 indexed citations
2.
Gross, Sean M., et al.. (2023). MOBILE pipeline enables identification of context-specific networks and regulatory mechanisms. Nature Communications. 14(1). 3991–3991. 2 indexed citations
3.
Gross, Sean M., et al.. (2023). Analysis and modeling of cancer drug responses using cell cycle phase-specific rate effects. Nature Communications. 14(1). 3450–3450. 25 indexed citations
4.
Copperman, Jeremy, Sean M. Gross, Young Hwan Chang, Laura M. Heiser, & Daniel M. Zuckerman. (2023). Morphodynamical cell state description via live-cell imaging trajectory embedding. Communications Biology. 6(1). 484–484. 9 indexed citations
5.
Ternes, Luke, Mark Dane, Sean M. Gross, et al.. (2022). A multi-encoder variational autoencoder controls multiple transformational features in single-cell image analysis. Communications Biology. 5(1). 255–255. 26 indexed citations
6.
Bouhaddou, Mehdi, Robert C. Blake, Sean M. Gross, et al.. (2022). A scalable, open-source implementation of a large-scale mechanistic model for single cell proliferation and death signaling. Nature Communications. 13(1). 3555–3555. 14 indexed citations
7.
Gross, Sean M., et al.. (2022). A lineage tree-based hidden Markov model quantifies cellular heterogeneity and plasticity. Communications Biology. 5(1). 1258–1258. 8 indexed citations
8.
Sung, Hye Kyoung, et al.. (2021). Iron overload reduces adiponectin receptor expression via a ROS/FOXO1‐dependent mechanism leading to adiponectin resistance in skeletal muscle cells. Journal of Cellular Physiology. 236(7). 5339–5351. 12 indexed citations
9.
Smith, Rebecca, Kaylyn L. Devlin, David Kilburn, et al.. (2019). Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer. Journal of Visualized Experiments. 9 indexed citations
10.
Gross, Sean M., Mark Dane, Elmar Bucher, & Laura M. Heiser. (2019). Individual Cells Can Resolve Variations in Stimulus Intensity along the IGF-PI3K-AKT Signaling Axis. Cell Systems. 9(6). 580–588.e4. 23 indexed citations
11.
Devlin, Kaylyn L., David Kilburn, Sean M. Gross, et al.. (2019). Using Microarrays to Interrogate Microenvironmental Impact on Cellular Phenotypes in Cancer. Journal of Visualized Experiments.
12.
Gross, Sean M. & Peter Rotwein. (2017). Quantification of growth factor signaling and pathway cross talk by live-cell imaging. American Journal of Physiology-Cell Physiology. 312(3). C328–C340. 13 indexed citations
13.
Gross, Sean M. & Peter Rotwein. (2016). Unraveling Growth Factor Signaling and Cell Cycle Progression in Individual Fibroblasts. Journal of Biological Chemistry. 291(28). 14628–14638. 22 indexed citations
14.
Gross, Sean M. & Peter Rotwein. (2016). Mapping growth-factor-modulated Akt signaling dynamics. Development. 143(11). e1.2–e1.2. 8 indexed citations
15.
Gross, Sean M. & Peter Rotwein. (2016). Mapping growth-factor-modulated Akt signaling dynamics. Journal of Cell Science. 129(10). 2052–2063. 31 indexed citations
16.
Gross, Sean M., et al.. (2015). Separating myoblast differentiation from muscle cell fusion using IGF-I and the p38 MAP kinase inhibitor SB202190. American Journal of Physiology-Cell Physiology. 309(7). C491–C500. 16 indexed citations
17.
Gross, Sean M. & Peter Rotwein. (2013). Live cell imaging reveals marked variability in myoblast proliferation and fate. Skeletal Muscle. 3(1). 10–10. 6 indexed citations
18.
Gross, Sean M. & Steven L. Lehman. (2013). Accessibility of Myofilament Cysteines and Effects on ATPase Depend on the Activation State during Exposure to Oxidants. PLoS ONE. 8(7). e69110–e69110. 18 indexed citations
19.
Rotwein, Peter, et al.. (2012). PL08 Deconstructing muscle differentiation: defining insulin-like growth factor actions in muscle development and repair. Growth Hormone & IGF Research. 22. S17–S17. 2 indexed citations
20.
Friedman, Lori S., Susan L. Gloor, Sean M. Gross, et al.. (2010). 79 Preclinical characterization of GDC-0068, a novel selective ATP competitive inhibitor of Akt. European Journal of Cancer Supplements. 8(7). 33–33.

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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