Kate L. White

2.6k total citations
46 papers, 1.5k citations indexed

About

Kate L. White is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Surgery. According to data from OpenAlex, Kate L. White has authored 46 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 14 papers in Cellular and Molecular Neuroscience and 11 papers in Surgery. Recurrent topics in Kate L. White's work include Neuropeptides and Animal Physiology (14 papers), Receptor Mechanisms and Signaling (13 papers) and Pancreatic function and diabetes (10 papers). Kate L. White is often cited by papers focused on Neuropeptides and Animal Physiology (14 papers), Receptor Mechanisms and Signaling (13 papers) and Pancreatic function and diabetes (10 papers). Kate L. White collaborates with scholars based in United States, China and United Kingdom. Kate L. White's co-authors include Raymond C. Stevens, Bryan L. Roth, Richard O. C. Oreffo, Kurt Wüthrich, Vsevolod Katritch, Matthew J. Dalby, Jordan K. Zjawiony, Prabhakar R. Polepally, Gye Won Han and Nikolaj Gadegaard and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Kate L. White

45 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kate L. White United States	19	1.0k	609	222	139	135	46	1.5k
Chenbo Zeng United States	29	1.8k 1.8×	417 0.7×	90 0.4×	119 0.9×	149 1.1×	40	2.4k
Matthew R. Whorton United States	14	1.8k 1.8×	971 1.6×	73 0.3×	180 1.3×	111 0.8×	21	2.1k
Anat Shirvan Israel	29	1.2k 1.2×	920 1.5×	113 0.5×	224 1.6×	68 0.5×	56	2.5k
Mei Cong United States	19	1.2k 1.2×	475 0.8×	75 0.3×	119 0.9×	49 0.4×	48	1.6k
Sonia Terrillon United States	12	1.2k 1.1×	684 1.1×	42 0.2×	120 0.9×	67 0.5×	17	1.6k
Sohum Mehta United States	25	1.9k 1.9×	437 0.7×	205 0.9×	88 0.6×	104 0.8×	58	2.5k
Yun‐Bi Lu China	26	847 0.8×	469 0.8×	290 1.3×	109 0.8×	94 0.7×	70	2.2k
Graham Ladds United Kingdom	23	1.2k 1.2×	437 0.7×	49 0.2×	74 0.5×	101 0.7×	99	1.7k
Krishna Ghosh India	28	1.4k 1.4×	768 1.3×	149 0.7×	119 0.9×	35 0.3×	69	2.1k
Kaleeckal G. Harikumar United States	28	1.8k 1.8×	1.2k 2.0×	38 0.2×	183 1.3×	234 1.7×	83	2.2k

Countries citing papers authored by Kate L. White

Since Specialization

Citations

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

Fields of papers citing papers by Kate L. White

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kate L. White

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

All Works

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20 of 20 papers shown

Yadav, Arun Kumar, et al.. (2026). Robust mitochondria segmentation and morphological profiling using soft X-ray tomography. Journal of Structural Biology. 218(1). 108291–108291.

Chang, Kevin, et al.. (2025). Secretory stimuli distinctly regulate insulin secretory granule maturation through structural remodeling. Structure. 33(11). 1831–1843.e4. 1 indexed citations

Chang, Kevin, et al.. (2024). Subcellular Feature-Based Classification of α and β Cells Using Soft X-ray Tomography. Cells. 13(10). 869–869. 4 indexed citations

Liu, Yameng, et al.. (2024). Insulator-based dielectrophoresis-assisted separation of insulin secretory vesicles. eLife. 13. 3 indexed citations

Klerk, Eleonora de, Christopher H. Emfinger, Mark P. Keller, et al.. (2023). Loss of ZNF148 enhances insulin secretion in human pancreatic β cells. JCI Insight. 8(11). 3 indexed citations

Singla, Jitin & Kate L. White. (2021). A community approach to whole-cell modeling. Current Opinion in Systems Biology. 26. 33–38. 7 indexed citations

Raveh, Barak, Kate L. White, Tanmoy Sanyal, et al.. (2021). Bayesian metamodeling of complex biological systems across varying representations. Proceedings of the National Academy of Sciences. 118(35). 25 indexed citations

Singla, Jitin, Kate L. White, Raymond C. Stevens, & Frank Alber. (2021). Assessment of scoring functions to rank the quality of 3D subtomogram clusters from cryo-electron tomography. Journal of Structural Biology. 213(2). 107727–107727. 2 indexed citations

White, Kate L., Jitin Singla, Valentina Loconte, et al.. (2020). Visualizing subcellular rearrangements in intact β cells using soft x-ray tomography. Science Advances. 6(50). 40 indexed citations

10.

Zhang, Xianjun, Stephen D. Carter, Jitin Singla, et al.. (2020). Visualizing insulin vesicle neighborhoods in β cells by cryo–electron tomography. Science Advances. 6(50). 25 indexed citations

11.

Yu, Jing, Véronique Blais, Nilkanth Patel, et al.. (2019). Elucidating the active δ-opioid receptor crystal structure with peptide and small-molecule agonists. Science Advances. 5(11). eaax9115–eaax9115. 86 indexed citations

12.

Singla, Jitin, Kyle M. McClary, Kate L. White, et al.. (2018). Opportunities and Challenges in Building a Spatiotemporal Multi-scale Model of the Human Pancreatic β Cell. Cell. 173(1). 11–19. 51 indexed citations

13.

White, Kate L., Matthew T. Eddy, Zhan‐Guo Gao, et al.. (2018). Structural Connection between Activation Microswitch and Allosteric Sodium Site in GPCR Signaling. Structure. 26(2). 259–269.e5. 124 indexed citations

14.

Eddy, Matthew T., Ming-Yue Lee, Zhan‐Guo Gao, et al.. (2017). Allosteric Coupling of Drug Binding and Intracellular Signaling in the A2A Adenosine Receptor. Cell. 172(1-2). 68–80.e12. 160 indexed citations

15.

Robinson, J. Elliott, Eyal Vardy, Jeffrey F. DiBerto, et al.. (2015). Receptor Reserve Moderates Mesolimbic Responses to Opioids in a Humanized Mouse Model of the OPRM1 A118G Polymorphism. Neuropsychopharmacology. 40(11). 2614–2622. 27 indexed citations

16.

Tsimbouri, Penelope M., Nikolaj Gadegaard, Karl Burgess, et al.. (2013). Nanotopographical Effects on Mesenchymal Stem Cell Morphology and Phenotype. Journal of Cellular Biochemistry. 115(2). 380–390. 96 indexed citations

17.

White, Kate L., et al.. (2013). Nanotopographical Cues Augment Mesenchymal Differentiation of Human Embryonic Stem Cells. Small. 9(12). 2140–2151. 72 indexed citations

18.

Polepally, Prabhakar R., Kate L. White, Eyal Vardy, et al.. (2013). Kappa-opioid receptor-selective dicarboxylic ester-derived salvinorin A ligands. Bioorganic & Medicinal Chemistry Letters. 23(10). 2860–2862. 17 indexed citations

19.

White, Kate L. & Bryan L. Roth. (2012). Psychotomimetic Effects of Kappa Opioid Receptor Agonists. Biological Psychiatry. 72(10). 797–798. 10 indexed citations

20.

Mitalipov, Shoukhrat, John D. Morrey, William A. Reed, & Kate L. White. (1998). Development of nuclear transfer and parthenogenetic rabbit embryos activated with inositol 1,4,5-trisphosphate. Theriogenology. 49(1). 324–324. 4 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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