Galina Marsh

599 total citations
8 papers, 359 citations indexed

About

Galina Marsh is a scholar working on Molecular Biology, Physiology and Neurology. According to data from OpenAlex, Galina Marsh has authored 8 papers receiving a total of 359 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Physiology and 2 papers in Neurology. Recurrent topics in Galina Marsh's work include Alzheimer's disease research and treatments (5 papers), CRISPR and Genetic Engineering (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). Galina Marsh is often cited by papers focused on Alzheimer's disease research and treatments (5 papers), CRISPR and Genetic Engineering (2 papers) and Neuroinflammation and Neurodegeneration Mechanisms (2 papers). Galina Marsh collaborates with scholars based in United States, Switzerland and Japan. Galina Marsh's co-authors include Michael Peterson, Richard M. Ransohoff, Andrea Crotti, Taylor L. Reynolds, Kathleen M. McAvoy, Ellen Cahir-McFarland, Karol Estrada, Andrew Cameron, Suzanne Szak and Ayla Ergün and has published in prestigious journals such as PLoS ONE, Scientific Reports and Neurobiology of Disease.

In The Last Decade

Galina Marsh

8 papers receiving 354 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Galina Marsh United States	7	152	148	121	100	95	8	359
Tomas Fanutza United States	9	158 1.0×	178 1.2×	60 0.5×	148 1.5×	122 1.3×	10	419
Andrea Wetzel United Kingdom	8	163 1.1×	119 0.8×	112 0.9×	52 0.5×	131 1.4×	9	372
Sissel Ida Schmidt Denmark	8	146 1.0×	65 0.4×	129 1.1×	66 0.7×	109 1.1×	12	317
Bavo Heeman Belgium	9	262 1.7×	145 1.0×	193 1.6×	77 0.8×	118 1.2×	10	492
Silvia De Cicco Germany	5	204 1.3×	134 0.9×	116 1.0×	74 0.7×	78 0.8×	5	427
Elisabeth L. Moussaud-Lamodière United States	7	265 1.7×	182 1.2×	276 2.3×	70 0.7×	122 1.3×	7	591
Zongbing Hao China	12	228 1.5×	96 0.6×	257 2.1×	68 0.7×	70 0.7×	18	530
Zied Landoulsi Tunisia	8	185 1.2×	69 0.5×	136 1.1×	190 1.9×	102 1.1×	16	421
Eugénie Mutez France	12	171 1.1×	74 0.5×	283 2.3×	74 0.7×	160 1.7×	28	427
Janani Parameswaran United States	8	202 1.3×	104 0.7×	159 1.3×	100 1.0×	130 1.4×	10	426

Countries citing papers authored by Galina Marsh

Since Specialization

Citations

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

Fields of papers citing papers by Galina Marsh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Galina Marsh

This figure shows the co-authorship network connecting the top 25 collaborators of Galina Marsh. A scholar is included among the top collaborators of Galina Marsh 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 Galina Marsh. Galina Marsh 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

Peterson, Michael, Helen McLaughlin, Eric Marshall, et al.. (2021). Highly efficient neuronal gene knockout in vivo by CRISPR-Cas9 via neonatal intracerebroventricular injection of AAV in mice. Gene Therapy. 28(10-11). 646–658. 34 indexed citations

Marsh, Galina, Shanqin Xu, Kathryn Koszka, et al.. (2021). Use of CRISPR/Cas9-mediated disruption of CNS cell type genes to profile transduction of AAV by neonatal intracerebroventricular delivery in mice. Gene Therapy. 28(7-8). 456–468. 13 indexed citations

Valencia, Antonio, Bekim Bajrami, Galina Marsh, et al.. (2021). Antisense Oligonucleotide-Mediated Reduction of HDAC6 Does Not Reduce Tau Pathology in P301S Tau Transgenic Mice. Frontiers in Neurology. 12. 624051–624051. 4 indexed citations

Merola, Joseph F., Wenting Wang, Carrie Wager, et al.. (2021). RNA tape sampling in cutaneous lupus erythematosus discriminates affected from unaffected and healthy volunteer skin. Lupus Science & Medicine. 8(1). e000428–e000428. 9 indexed citations

Taga, Mariko, Vladislav Petyuk, Charles C. White, et al.. (2020). BIN1 protein isoforms are differentially expressed in astrocytes, neurons, and microglia: neuronal and astrocyte BIN1 are implicated in tau pathology. Molecular Neurodegeneration. 15(1). 44–44. 35 indexed citations

McAvoy, Kathleen M., Galina Marsh, Michael Peterson, et al.. (2019). Cell-autonomous and non-cell autonomous effects of neuronal BIN1 loss in vivo. PLoS ONE. 14(8). e0220125–e0220125. 17 indexed citations

Crotti, Andrea, Kathleen M. McAvoy, Karol Estrada, et al.. (2019). BIN1 favors the spreading of Tau via extracellular vesicles. Scientific Reports. 9(1). 9477–9477. 111 indexed citations

Weihofen, Andreas, Yuting Liu, Joseph W. Arndt, et al.. (2018). Development of an aggregate-selective, human-derived α-synuclein antibody BIIB054 that ameliorates disease phenotypes in Parkinson's disease models. Neurobiology of Disease. 124. 276–288. 136 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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