Lucas T. Graybuck

12.2k total citations · 1 hit paper
8 papers, 1.6k citations indexed

About

Lucas T. Graybuck is a scholar working on Molecular Biology, Cognitive Neuroscience and Neurology. According to data from OpenAlex, Lucas T. Graybuck has authored 8 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Cognitive Neuroscience and 3 papers in Neurology. Recurrent topics in Lucas T. Graybuck's work include Single-cell and spatial transcriptomics (5 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers) and Neural dynamics and brain function (2 papers). Lucas T. Graybuck is often cited by papers focused on Single-cell and spatial transcriptomics (5 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers) and Neural dynamics and brain function (2 papers). Lucas T. Graybuck collaborates with scholars based in United States and France. Lucas T. Graybuck's co-authors include Bosiljka Tasic, Zizhen Yao, Paul Sample, Richard A. Muscat, Georg Seelig, Sumit Mukherjee, Drew L. Sellers, Wei Chen, Alexander Rosenberg and Anna Kuchina and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Lucas T. Graybuck

7 papers receiving 1.6k citations

Hit Papers

Single-cell profiling of the developing mouse brain and s... 2018 2026 2020 2023 2018 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Lucas T. Graybuck United States 7 1.1k 300 260 202 199 8 1.6k
Sam Vesuna United States 10 959 0.9× 332 1.1× 257 1.0× 124 0.6× 160 0.8× 14 1.5k
Emily Sylwestrak United States 9 1.2k 1.2× 531 1.8× 243 0.9× 136 0.7× 167 0.8× 9 1.7k
Mohan Bolisetty United States 14 1.2k 1.1× 194 0.6× 132 0.5× 255 1.3× 178 0.9× 18 1.8k
M. Aurel Nagy United States 12 810 0.8× 303 1.0× 177 0.7× 86 0.4× 203 1.0× 13 1.3k
Markus M. Hilscher Sweden 18 622 0.6× 329 1.1× 187 0.7× 92 0.5× 123 0.6× 30 1.0k
Rachel C. Bandler United States 10 656 0.6× 536 1.8× 260 1.0× 138 0.7× 93 0.5× 11 1.2k
Le Sun China 14 1.2k 1.1× 253 0.8× 159 0.6× 160 0.8× 103 0.5× 22 1.6k
Jesper Ryge Sweden 12 971 0.9× 506 1.7× 199 0.8× 95 0.5× 83 0.4× 16 1.5k
Lukasz Swiech Poland 14 1.3k 1.2× 389 1.3× 89 0.3× 99 0.5× 171 0.9× 17 1.9k
Georgi Tushev Germany 16 2.3k 2.1× 521 1.7× 173 0.7× 972 4.8× 105 0.5× 19 2.8k

Countries citing papers authored by Lucas T. Graybuck

Since Specialization
Citations

This map shows the geographic impact of Lucas T. Graybuck'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 Lucas T. Graybuck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lucas T. Graybuck more than expected).

Fields of papers citing papers by Lucas T. Graybuck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lucas T. Graybuck. 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 Lucas T. Graybuck. The network helps show where Lucas T. Graybuck may publish in the future.

Co-authorship network of co-authors of Lucas T. Graybuck

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

All Works

8 of 8 papers shown
1.
Vasaikar, Suhas, Adam K. Savage, Elliott Swanson, et al.. (2023). A comprehensive platform for analyzing longitudinal multi-omics data. Nature Communications. 14(1). 1684–1684. 21 indexed citations
2.
Swanson, Elliott, Julian Reading, Lucas T. Graybuck, & Peter J. Skene. (2022). BarWare: efficient software tools for barcoded single-cell genomics. BMC Bioinformatics. 23(1). 106–106.
3.
Swanson, Elliott, Cara Lord, Julian Reading, et al.. (2021). Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq. eLife. 10. 154 indexed citations
4.
Ding, Song‐Lin, Zizhen Yao, Karla E. Hirokawa, et al.. (2020). Distinct Transcriptomic Cell Types and Neural Circuits of the Subiculum and Prosubiculum along the Dorsal-Ventral Axis. Cell Reports. 31(7). 107648–107648. 49 indexed citations
5.
Smith, Stephen J, Uygar Sümbül, Lucas T. Graybuck, et al.. (2019). Single-cell transcriptomic evidence for dense intracortical neuropeptide networks. eLife. 8. 90 indexed citations
6.
Kim, Dong‐Wook, Zizhen Yao, Lucas T. Graybuck, et al.. (2019). Multimodal Analysis of Cell Types in a Hypothalamic Node Controlling Social Behavior. Cell. 179(3). 713–728.e17. 166 indexed citations
7.
Rosenberg, Alexander, Charles M. Roco, Richard A. Muscat, et al.. (2018). Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding. Science. 360(6385). 176–182. 877 indexed citations breakdown →
8.
Economo, Michael N., Sarada Viswanathan, Bosiljka Tasic, et al.. (2018). Distinct descending motor cortex pathways and their roles in movement. Nature. 563(7729). 79–84. 217 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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