Shanna L. Bowman

909 total citations
8 papers, 375 citations indexed

About

Shanna L. Bowman is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Cell Biology. According to data from OpenAlex, Shanna L. Bowman has authored 8 papers receiving a total of 375 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 4 papers in Cell Biology. Recurrent topics in Shanna L. Bowman's work include Receptor Mechanisms and Signaling (5 papers), Cellular transport and secretion (3 papers) and Neuropeptides and Animal Physiology (3 papers). Shanna L. Bowman is often cited by papers focused on Receptor Mechanisms and Signaling (5 papers), Cellular transport and secretion (3 papers) and Neuropeptides and Animal Physiology (3 papers). Shanna L. Bowman collaborates with scholars based in United States, France and Germany. Shanna L. Bowman's co-authors include Manojkumar A. Puthenveedu, Linh Le, Michael S. Marks, Jing Bi‐Karchin, Daniel J. Shiwarski, Roshanak Irannejad, Xufan Tian, Mark von Zastrow, Jeffrey Benovic and Yang Du and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Cell Biology and Cell Reports.

In The Last Decade

Shanna L. Bowman

8 papers receiving 371 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shanna L. Bowman United States	7	240	188	87	51	40	8	375
Arancha Rodrı́guez-Garcı́a Spain	6	271 1.1×	102 0.5×	80 0.9×	42 0.8×	40 1.0×	7	436
Svetlana A. Shestopal United States	11	283 1.2×	176 0.9×	77 0.9×	38 0.7×	29 0.7×	23	481
Nawal Kassas France	8	310 1.3×	207 1.1×	50 0.6×	63 1.2×	25 0.6×	11	400
Marina S. Gelman United States	11	431 1.8×	230 1.2×	110 1.3×	66 1.3×	46 1.1×	13	650
Kan Yu United States	9	563 2.3×	87 0.5×	131 1.5×	39 0.8×	35 0.9×	13	691
Melinda D. Hains United States	8	493 2.1×	106 0.6×	115 1.3×	36 0.7×	31 0.8×	9	622
Ryan A. Doan United States	4	185 0.8×	80 0.4×	111 1.3×	72 1.4×	29 0.7×	5	441
Éva Wisniewski United States	9	271 1.1×	191 1.0×	48 0.6×	74 1.5×	37 0.9×	13	421
Ademuyiwa S. Aromolaran United States	6	458 1.9×	153 0.8×	111 1.3×	38 0.7×	48 1.2×	15	591
Amy Brown Canada	4	266 1.1×	71 0.4×	55 0.6×	37 0.7×	30 0.8×	10	364

Countries citing papers authored by Shanna L. Bowman

Since Specialization

Citations

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

Fields of papers citing papers by Shanna L. Bowman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanna L. Bowman

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

All Works

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8 of 8 papers shown

Bowman, Shanna L., Linh Le, Yueyao Zhu, et al.. (2021). A BLOC-1–AP-3 super-complex sorts a cis-SNARE complex into endosome-derived tubular transport carriers. The Journal of Cell Biology. 220(7). 15 indexed citations

Bowman, Shanna L., Jing Bi‐Karchin, Linh Le, & Michael S. Marks. (2019). The road to lysosome‐related organelles: Insights from Hermansky‐Pudlak syndrome and other rare diseases. Traffic. 20(6). 404–435. 149 indexed citations

McGarvey, Jennifer C., Kunhong Xiao, Shanna L. Bowman, et al.. (2016). Actin-Sorting Nexin 27 (SNX27)-Retromer Complex Mediates Rapid Parathyroid Hormone Receptor Recycling. Journal of Biological Chemistry. 291(21). 10986–11002. 53 indexed citations

Tian, Xufan, Roshanak Irannejad, Shanna L. Bowman, et al.. (2016). The α-Arrestin ARRDC3 Regulates the Endosomal Residence Time and Intracellular Signaling of the β2-Adrenergic Receptor. Journal of Biological Chemistry. 291(28). 14510–14525. 52 indexed citations

Bowman, Shanna L., Daniel J. Shiwarski, & Manojkumar A. Puthenveedu. (2016). Distinct G protein–coupled receptor recycling pathways allow spatial control of downstream G protein signaling. The Journal of Cell Biology. 214(7). 797–806. 59 indexed citations

Bowman, Shanna L., et al.. (2015). Cell-Autonomous Regulation of Mu-Opioid Receptor Recycling by Substance P. Cell Reports. 10(11). 1925–1936. 29 indexed citations

Bowman, Shanna L. & Manojkumar A. Puthenveedu. (2015). Postendocytic Sorting of Adrenergic and Opioid Receptors. Progress in molecular biology and translational science. 132. 189–206. 16 indexed citations

Bowman, Shanna L., et al.. (2015). Visualizing and quantitating sequence-dependent GPCR recycling. Methods in cell biology. 130. 333–345. 2 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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