Roy Wollman

4.6k total citations
49 papers, 3.3k citations indexed

About

Roy Wollman is a scholar working on Molecular Biology, Cell Biology and Biophysics. According to data from OpenAlex, Roy Wollman has authored 49 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 13 papers in Cell Biology and 8 papers in Biophysics. Recurrent topics in Roy Wollman's work include Gene Regulatory Network Analysis (13 papers), Single-cell and spatial transcriptomics (11 papers) and Microtubule and mitosis dynamics (10 papers). Roy Wollman is often cited by papers focused on Gene Regulatory Network Analysis (13 papers), Single-cell and spatial transcriptomics (11 papers) and Microtubule and mitosis dynamics (10 papers). Roy Wollman collaborates with scholars based in United States, United Kingdom and Canada. Roy Wollman's co-authors include Jonathan M. Scholey, Tobias Meyer, Nico Stuurman, Ronald D. Vale, Gohta Goshima, Alex Mogilner, Anna Pilko, Nan Zhang, Sarah S. Goodwin and Kenneth B. Kaplan and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Roy Wollman

48 papers receiving 3.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Roy Wollman United States 27 2.5k 1.5k 387 282 244 49 3.3k
Marvin E. Tanenbaum Netherlands 30 4.0k 1.6× 1.9k 1.3× 312 0.8× 176 0.6× 421 1.7× 50 4.8k
Maria Pia Cosma Spain 36 3.5k 1.4× 548 0.4× 414 1.1× 259 0.9× 440 1.8× 85 4.6k
Yusuke Toyoda Japan 24 2.6k 1.0× 1.7k 1.2× 444 1.1× 95 0.3× 407 1.7× 51 3.7k
Nathalie Daigle Germany 25 3.5k 1.4× 915 0.6× 303 0.8× 620 2.2× 442 1.8× 31 4.4k
Nicholas Hamilton Australia 28 1.7k 0.7× 1.1k 0.7× 121 0.3× 298 1.1× 194 0.8× 89 3.1k
Joël Beaudouin Germany 22 2.9k 1.2× 675 0.5× 195 0.5× 438 1.6× 490 2.0× 28 3.7k
Sébastien Huet France 28 2.1k 0.8× 536 0.4× 320 0.8× 215 0.8× 159 0.7× 74 2.8k
Laura Trinkle‐Mulcahy Canada 32 3.7k 1.5× 1.2k 0.8× 250 0.6× 98 0.3× 224 0.9× 72 4.4k
Michał Biśta United States 17 1.5k 0.6× 921 0.6× 143 0.4× 285 1.0× 105 0.4× 20 2.5k
James B. Moseley United States 28 2.2k 0.9× 2.3k 1.6× 315 0.8× 255 0.9× 138 0.6× 53 3.4k

Countries citing papers authored by Roy Wollman

Since Specialization
Citations

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

Fields of papers citing papers by Roy Wollman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roy Wollman

This figure shows the co-authorship network connecting the top 25 collaborators of Roy Wollman. A scholar is included among the top collaborators of Roy Wollman 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 Roy Wollman. Roy Wollman 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.
Sheu, Katherine M., et al.. (2024). Dynamical and combinatorial coding by MAPK p38 and NFκB in the inflammatory response of macrophages. Molecular Systems Biology. 20(8). 898–932. 4 indexed citations
2.
Wollman, Roy, et al.. (2022). Quantifying the phenotypic information in mRNA abundance. Molecular Systems Biology. 18(8). e11001–e11001. 4 indexed citations
3.
Song, Dongyuan, et al.. (2021). scPNMF: sparse gene encoding of single cells to facilitate gene selection for targeted gene profiling. Bioinformatics. 37(Supplement_1). i358–i366. 13 indexed citations
4.
Littman, Russell, Rob Foreman, Douglas Arneson, et al.. (2021). Joint cell segmentation and cell type annotation for spatial transcriptomics. Molecular Systems Biology. 17(6). e10108–e10108. 57 indexed citations
5.
Wollman, Roy, et al.. (2021). Bridging scales: From cell biology to physiology using in situ single-cell technologies. Cell Systems. 12(5). 388–400. 11 indexed citations
6.
Tang, Ying, et al.. (2021). Quantifying information accumulation encoded in the dynamics of biochemical signaling. Nature Communications. 12(1). 1272–1272. 27 indexed citations
7.
Pilko, Anna, et al.. (2020). Loci specific epigenetic drug sensitivity. Nucleic Acids Research. 48(9). 4797–4810. 6 indexed citations
8.
Foreman, Rob, et al.. (2020). Identifying chromatin features that regulate gene expression distribution. Scientific Reports. 10(1). 20566–20566. 5 indexed citations
9.
Gan, Lin, Akiko Seki, Kimberle Shen, et al.. (2019). The lysosomal GPCR-like protein GPR137B regulates Rag and mTORC1 localization and activity. Nature Cell Biology. 21(5). 614–626. 32 indexed citations
10.
Wollman, Roy, et al.. (2017). Wound-induced Ca 2+ wave propagates through a simple release and diffusion mechanism. Molecular Biology of the Cell. 28(11). 1457–1466. 30 indexed citations
11.
Yao, Jason, Anna Pilko, & Roy Wollman. (2016). Distinct cellular states determine calcium signaling response. Molecular Systems Biology. 12(12). 894–894. 49 indexed citations
12.
Yao, Jason, et al.. (2016). Signal Transduction at the Single-Cell Level: Approaches to Study the Dynamic Nature of Signaling Networks. Journal of Molecular Biology. 428(19). 3669–3682. 27 indexed citations
13.
Selimkhanov, Jangir, Brooks Taylor, Jason Yao, et al.. (2014). Accurate information transmission through dynamic biochemical signaling networks. Science. 346(6215). 1370–1373. 262 indexed citations
14.
Wollman, Roy & Tobias Meyer. (2012). Coordinated oscillations in cortical actin and Ca2+ correlate with cycles of vesicle secretion. Nature Cell Biology. 14(12). 1261–1269. 101 indexed citations
15.
Santos, Silvia, Roy Wollman, Tobias Meyer, & James E. Ferrell. (2012). Spatial Positive Feedback at the Onset of Mitosis. Cell. 149(7). 1500–1513. 111 indexed citations
16.
Wollman, Roy, Gul Civelekoglu‐Scholey, Jonathan M. Scholey, & Alex Mogilner. (2008). Reverse engineering of force integration during mitosis in the Drosophila embryo. Molecular Systems Biology. 4(1). 195–195. 46 indexed citations
17.
Goshima, Gohta, Roy Wollman, Sarah S. Goodwin, et al.. (2007). Genes Required for Mitotic Spindle Assembly in Drosophila S2 Cells. Science. 316(5823). 417–421. 450 indexed citations
18.
Green, Rebecca A., Roy Wollman, & Kenneth B. Kaplan. (2005). APC and EB1 Function Together in Mitosis to Regulate Spindle Dynamics and Chromosome Alignment. Molecular Biology of the Cell. 16(10). 4609–4622. 180 indexed citations
19.
Wollman, Roy, Eric N. Cytrynbaum, Joshua T. Jones, et al.. (2005). Efficient Chromosome Capture Requires a Bias in the ‘Search-and-Capture’ Process during Mitotic-Spindle Assembly. Current Biology. 15(9). 828–832. 203 indexed citations
20.
Gutman, Roee, et al.. (2005). QuasiMotiFinder: protein annotation by searching for evolutionarily conserved motif-like patterns. Nucleic Acids Research. 33(Web Server). W255–W261. 28 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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