Katie McDole

2.9k total citations
21 papers, 1.8k citations indexed

About

Katie McDole is a scholar working on Molecular Biology, Biophysics and Biomedical Engineering. According to data from OpenAlex, Katie McDole has authored 21 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 10 papers in Biophysics and 3 papers in Biomedical Engineering. Recurrent topics in Katie McDole's work include Cell Image Analysis Techniques (9 papers), Pluripotent Stem Cells Research (7 papers) and Single-cell and spatial transcriptomics (7 papers). Katie McDole is often cited by papers focused on Cell Image Analysis Techniques (9 papers), Pluripotent Stem Cells Research (7 papers) and Single-cell and spatial transcriptomics (7 papers). Katie McDole collaborates with scholars based in United States, United Kingdom and Germany. Katie McDole's co-authors include Philipp Keller, William C. Lemon, Yinan Wan, Fernando Amat, Kristin Branson, Yixian Zheng, Léo Guignard, Srinivas C. Turaga, Löıc A. Royer and Grégoire Malandain and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Katie McDole

20 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Katie McDole United States 15 1.1k 662 294 273 137 21 1.8k
Nadine Peyriéras France 26 1.3k 1.2× 440 0.7× 242 0.8× 573 2.1× 107 0.8× 71 2.3k
Winfried Wiegraebe United States 9 1.1k 1.0× 448 0.7× 187 0.6× 269 1.0× 160 1.2× 11 2.1k
Dimitri Perrin Australia 13 884 0.8× 667 1.0× 329 1.1× 164 0.6× 329 2.4× 47 2.2k
Johannes Stegmaier Germany 16 842 0.8× 259 0.4× 150 0.5× 250 0.9× 183 1.3× 52 1.6k
Yinan Wan United States 15 606 0.5× 649 1.0× 200 0.7× 178 0.7× 94 0.7× 18 1.2k
Oliver Biehlmaier Switzerland 18 1.1k 1.0× 529 0.8× 308 1.0× 614 2.2× 377 2.8× 29 2.1k
Tim Wang China 2 877 0.8× 638 1.0× 173 0.6× 205 0.8× 141 1.0× 5 1.7k
Heejin Choi United States 17 647 0.6× 507 0.8× 352 1.2× 102 0.4× 221 1.6× 39 1.5k
Ashkan Javaherian United States 15 1.2k 1.1× 311 0.5× 290 1.0× 164 0.6× 446 3.3× 18 2.0k
Douglas S. Richardson United States 18 729 0.7× 602 0.9× 354 1.2× 189 0.7× 159 1.2× 37 1.8k

Countries citing papers authored by Katie McDole

Since Specialization
Citations

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

Fields of papers citing papers by Katie McDole

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Katie McDole

This figure shows the co-authorship network connecting the top 25 collaborators of Katie McDole. A scholar is included among the top collaborators of Katie McDole 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 Katie McDole. Katie McDole 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.
McDole, Katie, Juan de Dios Hourcade, Susana Temiño, et al.. (2025). Myocardium and endocardium of the early mammalian heart tube arise from independent multipotent lineages specified at the primitive streak. Developmental Cell. 60(18). 2434–2444.e5. 1 indexed citations
2.
Goodwin, Katharine, et al.. (2025). Organizer activity in the mouse embryo. PubMed. 184. 204001–204001.
3.
Wolf, Steffen, et al.. (2023). Unsupervised Learning of Object-Centric Embeddings for Cell Instance Segmentation in Microscopy Images. 21206–21215. 1 indexed citations
4.
Mönke, Gregor, et al.. (2022). Imaging the onset of oscillatory signaling dynamics during mouse embryo gastrulation. Development. 149(13). 13 indexed citations
5.
Hirsch, P. B., Léo Guignard, Katie McDole, et al.. (2022). Automated reconstruction of whole-embryo cell lineages by learning from sparse annotations. Nature Biotechnology. 41(1). 44–49. 16 indexed citations
6.
Vetter, Roman, et al.. (2022). Hinge point emergence in mammalian spinal neurulation. Proceedings of the National Academy of Sciences. 119(20). e2117075119–e2117075119. 13 indexed citations
7.
Tyser, Richard C. V., Ximena Ibarra-Soria, Katie McDole, et al.. (2021). Characterization of a common progenitor pool of the epicardium and myocardium. Science. 371(6533). 100 indexed citations
8.
Stelzer, Ernst H. K., Frederic Strobl, Bo-Jui Chang, et al.. (2021). Light sheet fluorescence microscopy. Nature Reviews Methods Primers. 1(1). 183 indexed citations
9.
Benito-Kwiecinski, Silvia, Stefano L. Giandomenico, Magdalena Sutcliffe, et al.. (2021). An early cell shape transition drives evolutionary expansion of the human forebrain. Cell. 184(8). 2084–2102.e19. 154 indexed citations
10.
Wolf, Steffen, Yinan Wan, & Katie McDole. (2021). Current approaches to fate mapping and lineage tracing using image data. Development. 148(18). 14 indexed citations
11.
Lemon, William C. & Katie McDole. (2020). Live-cell imaging in the era of too many microscopes. Current Opinion in Cell Biology. 66. 34–42. 45 indexed citations
12.
McDole, Katie, Léo Guignard, Fernando Amat, et al.. (2018). In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level. Cell. 175(3). 859–876.e33. 312 indexed citations
13.
Stegmaier, Johannes, Fernando Amat, William C. Lemon, et al.. (2016). Real-Time Three-Dimensional Cell Segmentation in Large-Scale Microscopy Data of Developing Embryos. Developmental Cell. 36(2). 225–240. 114 indexed citations
14.
Lemon, William C., Stefan R. Pulver, Burkhard Höckendorf, et al.. (2015). Whole-central nervous system functional imaging in larval Drosophila. Nature Communications. 6(1). 7924–7924. 137 indexed citations
15.
Amat, Fernando, Burkhard Höckendorf, Yinan Wan, et al.. (2015). Efficient processing and analysis of large-scale light-sheet microscopy data. Nature Protocols. 10(11). 1679–1696. 85 indexed citations
16.
Amat, Fernando, William C. Lemon, Daniel P. Mossing, et al.. (2014). Fast, accurate reconstruction of cell lineages from large-scale fluorescence microscopy data. Nature Methods. 11(9). 951–958. 196 indexed citations
17.
Kim, Young‐Jo, Katie McDole, & Yixian Zheng. (2012). The function of lamins in the context of tissue building and maintenance. Nucleus. 3(3). 256–262. 8 indexed citations
18.
McDole, Katie & Yixian Zheng. (2012). Generation and live imaging of an endogenous Cdx2 reporter mouse line. genesis. 50(10). 775–782. 34 indexed citations
19.
Kim, Young‐Jo, Alexei A. Sharov, Katie McDole, et al.. (2011). Mouse B-Type Lamins Are Required for Proper Organogenesis But Not by Embryonic Stem Cells. Science. 334(6063). 1706–1710. 197 indexed citations
20.
McDole, Katie, Yuan Xiong, Pablo A. Iglesias, & Yixian Zheng. (2011). Lineage mapping the pre-implantation mouse embryo by two-photon microscopy, new insights into the segregation of cell fates. Developmental Biology. 355(2). 239–249. 74 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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