José Ignacio Gallea

732 total citations
17 papers, 544 citations indexed

About

José Ignacio Gallea is a scholar working on Biophysics, Neurology and Physiology. According to data from OpenAlex, José Ignacio Gallea has authored 17 papers receiving a total of 544 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Biophysics, 6 papers in Neurology and 6 papers in Physiology. Recurrent topics in José Ignacio Gallea's work include Advanced Fluorescence Microscopy Techniques (8 papers), Parkinson's Disease Mechanisms and Treatments (6 papers) and Alzheimer's disease research and treatments (5 papers). José Ignacio Gallea is often cited by papers focused on Advanced Fluorescence Microscopy Techniques (8 papers), Parkinson's Disease Mechanisms and Treatments (6 papers) and Alzheimer's disease research and treatments (5 papers). José Ignacio Gallea collaborates with scholars based in Germany, Argentina and United States. José Ignacio Gallea's co-authors include M. Soledad Celej, Rabia Sarroukh, Vincent Raussens, Jean‐Marie Ruysschaert, Adelin Gustot, Javier María Peralta Ramos, Claudio Bussi, Pablo Iribarren, Daniela S. Arroyo and Leonardo Adrián Medrano and has published in prestigious journals such as Advanced Materials, Journal of Biological Chemistry and Angewandte Chemie International Edition.

In The Last Decade

José Ignacio Gallea

17 papers receiving 539 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
José Ignacio Gallea Germany	11	211	180	168	135	104	17	544
Charles Ducrot Canada	10	94 0.4×	267 1.5×	215 1.3×	105 0.8×	86 0.8×	17	601
Kiyoshi Egami United States	13	175 0.8×	436 2.4×	375 2.2×	64 0.5×	163 1.6×	13	906
Jennifer Stine Elam United States	11	112 0.5×	247 1.4×	293 1.7×	96 0.7×	55 0.5×	13	983
Matthew Byrne United States	9	131 0.6×	101 0.6×	251 1.5×	98 0.7×	21 0.2×	14	442
Andreas Müller‐Schiffmann Germany	16	346 1.6×	391 2.2×	90 0.5×	107 0.8×	81 0.8×	29	800
Sofia Lövestam United Kingdom	9	497 2.4×	454 2.5×	150 0.9×	93 0.7×	16 0.2×	15	788
Ji Luo United States	18	176 0.8×	549 3.0×	100 0.6×	48 0.4×	127 1.2×	40	1.1k
Nicolette S. Honson Canada	15	180 0.9×	202 1.1×	36 0.2×	37 0.3×	60 0.6×	18	529
Vinod Udayar Switzerland	5	135 0.6×	112 0.6×	28 0.2×	15 0.1×	39 0.4×	9	284
Ruth Starwalt United States	6	71 0.3×	210 1.2×	47 0.3×	28 0.2×	40 0.4×	6	456

Countries citing papers authored by José Ignacio Gallea

Since Specialization

Citations

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

Fields of papers citing papers by José Ignacio Gallea

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José Ignacio Gallea. 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 José Ignacio Gallea. The network helps show where José Ignacio Gallea may publish in the future.

Co-authorship network of co-authors of José Ignacio Gallea

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

All Works

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17 of 17 papers shown

Wang, Dongxia, José Ignacio Gallea, De‐Ming Kong, Jörg Enderlein, & Tao Chen. (2025). Super‐Resolution Axial Imaging for Quantifying Piconewton Traction Forces in Live Cells. Angewandte Chemie International Edition. 64(41). e202506864–e202506864. 1 indexed citations

Basak, Samrat, Alexey I. Chizhik, José Ignacio Gallea, et al.. (2025). Super-resolution optical fluctuation imaging. Nature Photonics. 19(3). 229–237. 8 indexed citations

Gallea, José Ignacio, Oleksii Nevskyi, Zuzanna Kaźmierczak, et al.. (2025). Super‐Resolution Goes Viral: T4 Virus Particles as Versatile 3D‐Bio‐NanoRulers. Advanced Materials. 37(12). e2403365–e2403365. 1 indexed citations

Chizhik, Alexey I., et al.. (2025). Molecular Level Super-Resolution Fluorescence Imaging. Annual Review of Biophysics. 54(1). 163–184. 1 indexed citations

Nevskyi, Oleksii, José Ignacio Gallea, Jan Christoph Thiele, et al.. (2024). Doubling the resolution of fluorescence-lifetime single-molecule localization microscopy with image scanning microscopy. Nature Photonics. 18(10). 1059–1066. 19 indexed citations

Nevskyi, Oleksii, et al.. (2024). Doubling the resolution of single-molecule localization microscopy with image scanning microscopy. GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen). 16–16. 1 indexed citations

Oleksiievets, Nazar, Jan Christoph Thiele, José Ignacio Gallea, et al.. (2022). Single-Molecule Fluorescence Lifetime Imaging Using Wide-Field and Confocal-Laser Scanning Microscopy: A Comparative Analysis. Nano Letters. 22(15). 6454–6461. 41 indexed citations

Hollingsworth, Jennifer A., et al.. (2022). Excited state lifetime modulation in semiconductor nanocrystals for super-resolution imaging. Nanotechnology. 33(36). 365201–365201. 1 indexed citations

Gallea, José Ignacio, et al.. (2021). Work-Related Mental Health Issues in Graduate Student Population. Frontiers in Neuroscience. 15. 593562–593562. 26 indexed citations

10.

Gallea, José Ignacio, et al.. (2020). From Work Well-Being to Burnout: A Hypothetical Phase Model. Frontiers in Neuroscience. 14. 360–360. 11 indexed citations

11.

Bussi, Claudio, Javier María Peralta Ramos, Daniela S. Arroyo, et al.. (2018). Alpha-synuclein fibrils recruit TBK1 and OPTN to lysosomal damage sites and induce autophagy in microglial cells. Journal of Cell Science. 131(23). 50 indexed citations

12.

Gallea, José Ignacio, et al.. (2018). Amyloid oligomerization of the Parkinson's disease related protein α‐synuclein impacts on its curvature‐membrane sensitivity. Journal of Neurochemistry. 147(4). 541–556. 10 indexed citations

13.

Bussi, Claudio, Javier María Peralta Ramos, Daniela S. Arroyo, et al.. (2017). Autophagy down regulates pro-inflammatory mediators in BV2 microglial cells and rescues both LPS and alpha-synuclein induced neuronal cell death. Scientific Reports. 7(1). 43153–43153. 83 indexed citations

14.

Gallea, José Ignacio, et al.. (2016). Structural remodeling during amyloidogenesis of physiological Nα-acetylated α-synuclein. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 1864(5). 501–510. 12 indexed citations

15.

Gustot, Adelin, José Ignacio Gallea, Rabia Sarroukh, et al.. (2015). Amyloid fibrils are the molecular trigger of inflammation in Parkinson's disease. Biochemical Journal. 471(3). 323–333. 141 indexed citations

16.

Gallea, José Ignacio & M. Soledad Celej. (2014). Structural Insights into Amyloid Oligomers of the Parkinson Disease-related Protein α-Synuclein. Journal of Biological Chemistry. 289(39). 26733–26742. 48 indexed citations

17.

Smith, Benjamin R., Michael S. Marshall, Ludovico Cantuti‐Castelvetri, et al.. (2014). Neuronal inclusions of α‐synuclein contribute to the pathogenesis of Krabbe disease. The Journal of Pathology. 232(5). 509–521. 90 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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