Mark Dane

872 citations
13 papers · 169 · h-index 8

Impact in

  • Biophysics top 10%
    • Cell Image Analysis Techniques
    • HER2/EGFR in Cancer Research
    • Cancer Cells and Metastasis

Papers in

    • Single-cell and spatial transcriptomics 4
    • Gene expression and cancer classification 2
    • Advanced Biosensing Techniques and Applications 2
    • Gene Regulatory Network Analysis 2
    • Cell Image Analysis Techniques 4
    • Advanced Fluorescence Microscopy Techniques 2

Mark Dane

12 papers receiving 164 citations

Peers

Mark Dane
Comparison fields: 5 of 67
  • Biophysics 31
  • Oncology 41
  • Cancer Research 21
  • Modeling and Simulation 6
  • Molecular Biology 89
Replace Sean M. Gross with:
Sean M. Gross United States
Edgar Cardenas De La Hoz Belgium
Benjamin Cappe France
Nicholas Trahearn United Kingdom
Lily A. Chylek United States
Yuko Saeki Japan
Sathya Muralidhar United Kingdom
Lotte Bruens Netherlands
Mia Niklasson Sweden
Santhosh Palani United States
Mark Dane relative to Sean M. Gross United States Sean M. Gross's profile →
Citations per field
00.5×1.6×
Sean M. Gross · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Mark Dane, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mark Dane Line = papers co-authored together Mark Dane links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 201850
2 202226
3 202325
4 201923
5 202211
6 20199
7 20208
8 20178
9 20206
10 20221
11 20191
12 20251
13 20190

About Mark Dane

Mark Dane is a scholar working on Molecular Biology, Biophysics, Oncology, Spectroscopy and Cellular and Molecular Neuroscience, having authored 13 papers that have together received 169 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (4 papers), Cell Image Analysis Techniques (4 papers), Advanced Fluorescence Microscopy Techniques (2 papers), Advanced Proteomics Techniques and Applications (2 papers), Gene expression and cancer classification (2 papers), Advanced Biosensing Techniques and Applications (2 papers), Gene Regulatory Network Analysis (2 papers) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Biophysics (31 citations), Oncology (41 citations), Cancer Research (21 citations), Modeling and Simulation (6 citations) and Molecular Biology (89 citations). Mark Dane has collaborated with scholars based in United States. Frequent co-authors include Laura M. Heiser, Sean M. Gross, Elmar Bucher, Joe W. Gray, Tiera Liby, James E. Korkola, Gordon B. Mills, David Kilburn, Rebecca Smith and Michel Nederlof. Their work appears in journals such as Cell Systems, Journal of Visualized Experiments, Scientific Reports, Human Molecular Genetics and Bioinformatics.

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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