Mark Dane

872 total citations
13 papers, 169 citations indexed

About

Mark Dane is a scholar working on Molecular Biology, Biophysics and Oncology. According to data from OpenAlex, Mark Dane has authored 13 papers receiving a total of 169 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 4 papers in Biophysics and 2 papers in Oncology. Recurrent topics in Mark Dane's work include Single-cell and spatial transcriptomics (4 papers), Cell Image Analysis Techniques (4 papers) and Advanced Biosensing Techniques and Applications (2 papers). Mark Dane is often cited by papers focused on Single-cell and spatial transcriptomics (4 papers), Cell Image Analysis Techniques (4 papers) and Advanced Biosensing Techniques and Applications (2 papers). Mark Dane collaborates with scholars based in United States. Mark Dane's co-authors include Laura M. Heiser, Sean M. Gross, Elmar Bucher, Joe W. Gray, James E. Korkola, Gordon B. Mills, Tiera Liby, Damir Sudar, Rebecca Smith and Michel Nederlof and has published in prestigious journals such as Nature Communications, Bioinformatics and Cancer Research.

In The Last Decade

Mark Dane

12 papers receiving 164 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mark Dane United States	8	89	41	31	23	21	13	169
Nicola Bougen‐Zhukov New Zealand	7	125 1.4×	55 1.3×	31 1.0×	6 0.3×	39 1.9×	11	208
Yuko Saeki Japan	8	278 3.1×	48 1.2×	43 1.4×	25 1.1×	21 1.0×	10	339
Sean M. Gross United States	12	215 2.4×	37 0.9×	49 1.6×	10 0.4×	13 0.6×	23	315
Ravian L. van Ineveld Netherlands	5	115 1.3×	48 1.2×	43 1.4×	8 0.3×	28 1.3×	9	181
Lotte Bruens Netherlands	7	121 1.4×	89 2.2×	18 0.6×	10 0.4×	35 1.7×	9	248
Benjamin Cappe France	6	151 1.7×	55 1.3×	20 0.6×	22 1.0×	61 2.9×	8	243
Leandra Sepe Italy	8	198 2.2×	44 1.1×	15 0.5×	11 0.5×	33 1.6×	18	312
Connor Stashko United States	7	87 1.0×	62 1.5×	59 1.9×	33 1.4×	37 1.8×	7	271
Michael S. Nelson United States	8	73 0.8×	49 1.2×	7 0.2×	8 0.3×	23 1.1×	18	159
Cristiano Guttà Germany	9	196 2.2×	33 0.8×	8 0.3×	15 0.7×	40 1.9×	10	288

Countries citing papers authored by Mark Dane

Since Specialization

Citations

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

Fields of papers citing papers by Mark Dane

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Dane

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

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

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

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

Hunt, Gregory J., Mark Dane, James E. Korkola, Laura M. Heiser, & Johann A. Gagnon-Bartsch. (2022). Systematic replication enables normalization of high-throughput imaging assays. Bioinformatics. 38(21). 4934–4940. 1 indexed citations

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

Hernandez, Sarah, Ryan G. Lim, Mark Dane, et al.. (2022). An altered extracellular matrix–integrin interface contributes to Huntington’s disease-associated CNS dysfunction in glial and vascular cells. Human Molecular Genetics. 32(9). 1483–1496. 11 indexed citations

Dane, Mark, et al.. (2020). Integrating Mathematical Modeling with High-Throughput Imaging Explains How Polyploid Populations Behave in Nutrient-Sparse Environments. Cancer Research. 80(22). 5109–5120. 8 indexed citations

Hunt, Gregory J., Mark Dane, James E. Korkola, Laura M. Heiser, & Johann A. Gagnon-Bartsch. (2020). Automatic Transformation and Integration to Improve Visualization and Discovery of Latent Effects in Imaging Data. Journal of Computational and Graphical Statistics. 29(4). 929–941. 6 indexed citations

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

Dane, Mark, et al.. (2019). Variational autoencoding tissue response to microenvironment perturbation. PubMed. 10949. 1 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.

Watson, Spencer S., Mark Dane, Koei Chin, et al.. (2018). Microenvironment-Mediated Mechanisms of Resistance to HER2 Inhibitors Differ between HER2+ Breast Cancer Subtypes. Cell Systems. 6(3). 329–342.e6. 50 indexed citations

13.

Schwartzman, Jacob, Daniel J. Coleman, Nicholas J. Wang, et al.. (2017). Integrative molecular network analysis identifies emergent enzalutamide resistance mechanisms in prostate cancer. Oncotarget. 8(67). 111084–111095. 8 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.

Explore authors with similar magnitude of impact