Kate G. Storey

6.3k total citations
65 papers, 4.8k citations indexed

About

Kate G. Storey is a scholar working on Molecular Biology, Cell Biology and Developmental Neuroscience. According to data from OpenAlex, Kate G. Storey has authored 65 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 19 papers in Cell Biology and 15 papers in Developmental Neuroscience. Recurrent topics in Kate G. Storey's work include Developmental Biology and Gene Regulation (36 papers), Congenital heart defects research (16 papers) and Neurogenesis and neuroplasticity mechanisms (15 papers). Kate G. Storey is often cited by papers focused on Developmental Biology and Gene Regulation (36 papers), Congenital heart defects research (16 papers) and Neurogenesis and neuroplasticity mechanisms (15 papers). Kate G. Storey collaborates with scholars based in United Kingdom, United States and Portugal. Kate G. Storey's co-authors include Isabel Olivera-Martínez, Ruth Díez del Corral, Claudio D. Stern, Raman M Das, Valerie Wilson, J. Simon Lunn, Marios P. Stavridis, Anne Goriely, Edward M. De Robertis and Barry Collins and has published in prestigious journals such as Science, Cell and Neuron.

In The Last Decade

Kate G. Storey

64 papers receiving 4.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kate G. Storey United Kingdom 36 4.3k 876 830 800 515 65 4.8k
Jeremy S. Dasen United States 31 3.2k 0.7× 964 1.1× 628 0.8× 761 1.0× 884 1.7× 49 4.8k
Brian Ciruna Canada 26 3.3k 0.8× 974 1.1× 532 0.6× 1.1k 1.4× 430 0.8× 45 4.3k
Harukazu Nakamura Japan 39 3.7k 0.9× 969 1.1× 700 0.8× 704 0.9× 1.3k 2.5× 128 4.7k
Ronald A. Conlon United States 31 4.9k 1.1× 1.0k 1.2× 616 0.7× 857 1.1× 710 1.4× 45 6.1k
Henk Roelink United States 32 6.0k 1.4× 1.5k 1.7× 1.1k 1.3× 692 0.9× 876 1.7× 53 6.6k
Jonas Muhr Sweden 26 2.9k 0.7× 716 0.8× 947 1.1× 377 0.5× 556 1.1× 33 3.5k
Ruth Ashery‐Padan Israel 44 4.7k 1.1× 1.1k 1.2× 782 0.9× 781 1.0× 905 1.8× 80 6.0k
Lauren Snider United States 23 4.1k 1.0× 762 0.9× 276 0.3× 368 0.5× 730 1.4× 33 4.7k
Valeria Marigo Italy 35 4.3k 1.0× 1.1k 1.2× 237 0.3× 638 0.8× 791 1.5× 88 5.0k
Anjen Chenn United States 26 2.6k 0.6× 660 0.8× 1.5k 1.8× 667 0.8× 1.0k 2.0× 43 4.0k

Countries citing papers authored by Kate G. Storey

Since Specialization
Citations

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

Fields of papers citing papers by Kate G. Storey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kate G. Storey. 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 Kate G. Storey. The network helps show where Kate G. Storey may publish in the future.

Co-authorship network of co-authors of Kate G. Storey

This figure shows the co-authorship network connecting the top 25 collaborators of Kate G. Storey. A scholar is included among the top collaborators of Kate G. Storey 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 Kate G. Storey. Kate G. Storey 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.
Llorens-Bobadilla, Enric, et al.. (2023). An ependymal cell census identifies heterogeneous and ongoing cell maturation in the adult mouse spinal cord that changes dynamically on injury. Developmental Cell. 58(3). 239–255.e10. 21 indexed citations
2.
Dady, Alwyn, et al.. (2022). A lateral protrusion latticework connects neuroepithelial cells and is regulated during neurogenesis. Journal of Cell Science. 135(6). 7 indexed citations
3.
Manning, Elizabeth, Mariyam Murtaza, Chris Hill, et al.. (2020). Crumbs2 mediates ventricular layer remodelling to form the spinal cord central canal. PLoS Biology. 18(3). e3000470–e3000470. 11 indexed citations
4.
Felts, Paul A., et al.. (2019). Multiple steps characterise ventricular layer attrition to form the ependymal cell lining of the adult mouse spinal cord central canal. Journal of Anatomy. 236(2). 334–350. 16 indexed citations
5.
Halley, Pamela A., Christopher Lipina, Marek Gierliński, et al.. (2019). Wnt regulates amino acid transporter Slc7a5 and so constrains the integrated stress response in mouse embryos. EMBO Reports. 21(1). e48469–e48469. 28 indexed citations
6.
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8.
Das, Raman M & Kate G. Storey. (2014). Apical Abscission Alters Cell Polarity and Dismantles the Primary Cilium During Neurogenesis. Science. 343(6167). 200–204. 134 indexed citations
9.
Rhinn, Muriel, Claudia I. Semprich, Pamela A. Halley, et al.. (2013). FGF Signalling Regulates Chromatin Organisation during Neural Differentiation via Mechanisms that Can Be Uncoupled from Transcription. PLoS Genetics. 9(7). e1003614–e1003614. 43 indexed citations
10.
Olivera-Martínez, Isabel, Hidekiyo Harada, Pamela A. Halley, & Kate G. Storey. (2012). Loss of FGF-Dependent Mesoderm Identity and Rise of Endogenous Retinoid Signalling Determine Cessation of Body Axis Elongation. PLoS Biology. 10(10). e1001415–e1001415. 121 indexed citations
11.
Fior, Rita, et al.. (2011). A novel reporter of notch signalling indicates regulated and random notch activation during vertebrate neurogenesis. BMC Biology. 9(1). 58–58. 32 indexed citations
12.
Fishwick, Katherine, et al.. (2009). Initiation of neuronal differentiation requires PI3-kinase/TOR signalling in the vertebrate neural tube. Developmental Biology. 338(2). 215–225. 49 indexed citations
13.
Das, Raman M, Gareth R. Howell, Elizabeth R. Farrell, et al.. (2006). A robust system for RNA interference in the chicken using a modified microRNA operon. Developmental Biology. 294(2). 554–563. 172 indexed citations
14.
Akai, Jun, et al.. (2005). FGF-dependent Notch signaling maintains the spinal cord stem zone. Genes & Development. 19(23). 2877–2887. 81 indexed citations
15.
Akai, Jun & Kate G. Storey. (2003). Brain or Brawn. Cell. 115(5). 510–512. 15 indexed citations
16.
Eblaghie, Maxwell C., J. Simon Lunn, Robin J. Dickinson, et al.. (2003). Negative Feedback Regulation of FGF Signaling Levels by Pyst1/MKP3 in Chick Embryos. Current Biology. 13(12). 1009–1018. 149 indexed citations
17.
Corral, Ruth Díez del, Isabel Olivera-Martínez, Anne Goriely, et al.. (2003). Opposing FGF and Retinoid Pathways Control Ventral Neural Pattern, Neuronal Differentiation, and Segmentation during Body Axis Extension. Neuron. 40(1). 65–79. 466 indexed citations
18.
Brown, Jennifer & Kate G. Storey. (2000). A region of the vertebrate neural plate in which neighbouring cells can adopt neural or epidermal fates. Current Biology. 10(14). 869–872. 88 indexed citations
19.
Goriely, Anne, Ruth Díez del Corral, & Kate G. Storey. (1999). c-Irx2 expression reveals an early subdivision of the neural plate in the chick embryo. Mechanisms of Development. 87(1-2). 203–206. 35 indexed citations
20.
Henrique, Domingos, David M. Tyler, Chris Kintner, et al.. (1997). cash4, a novel achaete-scute homolog induced by Hensen's node during generation of the posterior nervous system.. Genes & Development. 11(5). 603–615. 61 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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