Larissa Traxler

1.0k total citations
9 papers, 351 citations indexed

About

Larissa Traxler is a scholar working on Molecular Biology, Developmental Neuroscience and Cellular and Molecular Neuroscience. According to data from OpenAlex, Larissa Traxler has authored 9 papers receiving a total of 351 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Developmental Neuroscience and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Larissa Traxler's work include Pluripotent Stem Cells Research (4 papers), CRISPR and Genetic Engineering (3 papers) and Neurogenesis and neuroplasticity mechanisms (3 papers). Larissa Traxler is often cited by papers focused on Pluripotent Stem Cells Research (4 papers), CRISPR and Genetic Engineering (3 papers) and Neurogenesis and neuroplasticity mechanisms (3 papers). Larissa Traxler collaborates with scholars based in United States, Austria and Germany. Larissa Traxler's co-authors include Jérôme Mertens, Joseph R. Herdy, Fred H. Gage, Johannes C. M. Schlachetzki, Ravi Kant Agarwal, Christopher K. Glass, Frank Edenhofer, Angelo D’Alessandro, Davide Stefanoni and Doug Galasko and has published in prestigious journals such as Journal of Neuroscience, Cell Metabolism and FEBS Letters.

In The Last Decade

Larissa Traxler

9 papers receiving 349 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Larissa Traxler United States	8	208	126	80	67	38	9	351
Christopher Lovejoy United Kingdom	6	257 1.2×	157 1.2×	85 1.1×	51 0.8×	57 1.5×	10	415
Joaquim Duran‐Vilaregut Spain	9	194 0.9×	164 1.3×	118 1.5×	132 2.0×	32 0.8×	11	424
Jimena Baleriola Spain	10	291 1.4×	152 1.2×	140 1.8×	90 1.3×	47 1.2×	18	551
Wenjie Mao United States	10	291 1.4×	149 1.2×	117 1.5×	103 1.5×	28 0.7×	19	513
Dina Ivanyuk Germany	5	249 1.2×	125 1.0×	92 1.1×	86 1.3×	28 0.7×	6	476
Vasiliki Panagiotakopoulou Germany	7	278 1.3×	130 1.0×	109 1.4×	107 1.6×	45 1.2×	7	558
Sara Elmsaouri United States	5	171 0.8×	65 0.5×	51 0.6×	74 1.1×	15 0.4×	5	319
Karin Breu Switzerland	5	94 0.5×	192 1.5×	57 0.7×	55 0.8×	44 1.2×	6	345
Sachin S. Tiwari India	5	168 0.8×	87 0.7×	140 1.8×	116 1.7×	61 1.6×	8	351
Silvia De Cicco Germany	5	204 1.0×	134 1.1×	78 1.0×	74 1.1×	28 0.7×	5	427

Countries citing papers authored by Larissa Traxler

Since Specialization

Citations

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

Fields of papers citing papers by Larissa Traxler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Larissa Traxler

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

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

Traxler, Larissa, et al.. (2024). All roads lead to cholesterol: Modulating lipid biosynthesis in multiple sclerosis patient-derived models. Cell stem cell. 31(11). 1551–1552. 1 indexed citations

Traxler, Larissa, Raffaella Lucciola, Joseph R. Herdy, et al.. (2023). Neural cell state shifts and fate loss in ageing and age-related diseases. Nature Reviews Neurology. 19(7). 434–443. 10 indexed citations

Traxler, Larissa, Joseph R. Herdy, Davide Stefanoni, et al.. (2022). Warburg-like metabolic transformation underlies neuronal degeneration in sporadic Alzheimer’s disease. Cell Metabolism. 34(9). 1248–1263.e6. 96 indexed citations

Herdy, Joseph R., Larissa Traxler, Ravi Kant Agarwal, et al.. (2022). Increased post-mitotic senescence in aged human neurons is a pathological feature of Alzheimer’s disease. Cell stem cell. 29(12). 1637–1652.e6. 115 indexed citations

Böhnke, Lena, et al.. (2021). Direct Conversion of Human Fibroblasts to Induced Neurons. Methods in molecular biology. 2352. 73–96. 9 indexed citations

Traxler, Larissa, et al.. (2021). Metabolism navigates neural cell fate in development, aging and neurodegeneration. Disease Models & Mechanisms. 14(8). 26 indexed citations

Stanika, Ruslan I., Marta Campiglio, Daniele Repetto, et al.. (2019). Presynaptic α ₂ δ-2 Calcium Channel Subunits Regulate Postsynaptic GABA _A Receptor Abundance and Axonal Wiring. Journal of Neuroscience. 39(14). 2581–2605. 40 indexed citations

Traxler, Larissa, Frank Edenhofer, & Jérôme Mertens. (2019). Next‐generation disease modeling with direct conversion: a new path to old neurons. FEBS Letters. 593(23). 3316–3337. 38 indexed citations

Böhnke, Lena, Larissa Traxler, Joseph R. Herdy, & Jérôme Mertens. (2018). Human neurons to model aging: A dish best served old. Drug Discovery Today Disease Models. 27. 43–49. 16 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.

Explore authors with similar magnitude of impact