Ujjayini Ghosh

512 total citations
14 papers, 366 citations indexed

About

Ujjayini Ghosh is a scholar working on Molecular Biology, Physiology and Spectroscopy. According to data from OpenAlex, Ujjayini Ghosh has authored 14 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 6 papers in Physiology and 4 papers in Spectroscopy. Recurrent topics in Ujjayini Ghosh's work include Alzheimer's disease research and treatments (6 papers), Protein Structure and Dynamics (5 papers) and Lipid Membrane Structure and Behavior (5 papers). Ujjayini Ghosh is often cited by papers focused on Alzheimer's disease research and treatments (6 papers), Protein Structure and Dynamics (5 papers) and Lipid Membrane Structure and Behavior (5 papers). Ujjayini Ghosh collaborates with scholars based in United States, Sweden and Chile. Ujjayini Ghosh's co-authors include Robert Tycko, Kent R. Thurber, Wai‐Ming Yau, David P. Weliky, Myungwoon Lee, Masato Kato, Lihui Jia, Shuang Liang, John Collinge and Kelly Sackett and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nature Communications.

In The Last Decade

Ujjayini Ghosh

14 papers receiving 364 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ujjayini Ghosh United States	9	267	173	66	54	37	14	366
M. Schwalbe Germany	11	497 1.9×	257 1.5×	78 1.2×	24 0.4×	27 0.7×	12	674
Matthew R. Elkins United States	7	242 0.9×	103 0.6×	134 2.0×	25 0.5×	36 1.0×	8	372
Nadia El Mammeri United States	12	236 0.9×	162 0.9×	81 1.2×	44 0.8×	4 0.1×	19	404
Ivan Haralampiev Germany	11	209 0.8×	84 0.5×	21 0.3×	34 0.6×	27 0.7×	19	338
Mathias M. J. Bellaiche United Kingdom	7	224 0.8×	198 1.1×	16 0.2×	58 1.1×	10 0.3×	7	353
Narinder Sanghera United Kingdom	13	559 2.1×	123 0.7×	79 1.2×	22 0.4×	16 0.4×	17	695
Ioana M. Ilie Netherlands	13	276 1.0×	163 0.9×	27 0.4×	70 1.3×	4 0.1×	22	425
Alexandre Rhie United Kingdom	7	518 1.9×	54 0.3×	125 1.9×	23 0.4×	10 0.3×	7	628
Michael J. Bodkin United Kingdom	10	215 0.8×	102 0.6×	30 0.5×	15 0.3×	12 0.3×	18	360
Aaron M. Fluitt United States	8	281 1.1×	62 0.4×	35 0.5×	31 0.6×	11 0.3×	8	346

Countries citing papers authored by Ujjayini Ghosh

Since Specialization

Citations

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

Fields of papers citing papers by Ujjayini Ghosh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ujjayini Ghosh

This figure shows the co-authorship network connecting the top 25 collaborators of Ujjayini Ghosh. A scholar is included among the top collaborators of Ujjayini Ghosh 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 Ujjayini Ghosh. Ujjayini Ghosh 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:

14 of 14 papers shown

Ghosh, Ujjayini, Eric Tse, Hyunjun Yang, et al.. (2024). Cryo-EM structures reveal tau filaments from Down syndrome adopt Alzheimer’s disease fold. Acta Neuropathologica Communications. 12(1). 94–94. 8 indexed citations

Ghosh, Ujjayini, Wai‐Ming Yau, Nazaret Gamez, et al.. (2023). Two structurally defined Aβ polymorphs promote different pathological changes in susceptible mice. EMBO Reports. 24(8). e57003–e57003. 7 indexed citations

Zhang, Yijin, et al.. (2023). Lipid acyl chain protrusion induced by the influenza virus hemagglutinin fusion peptide detected by NMR paramagnetic relaxation enhancement. Biophysical Chemistry. 299. 107028–107028. 3 indexed citations

Wolfe, Robert, et al.. (2022). A large HIV gp41 construct with trimer-of-hairpins structure exhibits V2E mutation-dominant attenuation of vesicle fusion and helicity very similar to V2E attenuation of HIV fusion and infection and supports: (1) hairpin stabilization of membrane apposition with larger distance for V2E; and (2) V2E dominance by an antiparallel β sheet with interleaved fusion peptide strands from two gp41 trimers. Biophysical Chemistry. 293. 106933–106933. 1 indexed citations

Ghosh, Ujjayini, Kent R. Thurber, Wai‐Ming Yau, & Robert Tycko. (2021). Molecular structure of a prevalent amyloid-β fibril polymorph from Alzheimer's disease brain tissue. Proceedings of the National Academy of Sciences. 118(4). 125 indexed citations

Ghosh, Ujjayini & David P. Weliky. (2021). Rapid ²H NMR Transverse Relaxation of Perdeuterated Lipid Acyl Chains of Membrane with Bound Viral Fusion Peptide Supports Large-Amplitude Motions of These Chains That Can Catalyze Membrane Fusion. Biochemistry. 60(35). 2637–2651. 6 indexed citations

Ghosh, Ujjayini, Wai‐Ming Yau, John Collinge, & Robert Tycko. (2021). Structural differences in amyloid-β fibrils from brains of nondemented elderly individuals and Alzheimer's disease patients. Proceedings of the National Academy of Sciences. 118(45). 29 indexed citations

Ghosh, Ujjayini & David P. Weliky. (2020). 2H nuclear magnetic resonance spectroscopy supports larger amplitude fast motion and interference with lipid chain ordering for membrane that contains β sheet human immunodeficiency virus gp41 fusion peptide or helical hairpin influenza virus hemagglutinin fusion peptide at fusogenic pH. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1862(10). 183404–183404. 8 indexed citations

Lee, Myungwoon, Ujjayini Ghosh, Kent R. Thurber, Masato Kato, & Robert Tycko. (2020). Molecular structure and interactions within amyloid-like fibrils formed by a low-complexity protein sequence from FUS. Nature Communications. 11(1). 78 indexed citations

10.

Ghosh, Ujjayini, Wai‐Ming Yau, & Robert Tycko. (2018). Coexisting order and disorder within a common 40-residue amyloid-β fibril structure in Alzheimer's disease brain tissue. Chemical Communications. 54(40). 5070–5073. 22 indexed citations

11.

Jia, Lihui, et al.. (2015). REDOR solid-state NMR as a probe of the membrane locations of membrane-associated peptides and proteins. Journal of Magnetic Resonance. 253. 154–165. 22 indexed citations

12.

Ghosh, Ujjayini, et al.. (2015). Closed and Semiclosed Interhelical Structures in Membrane vs Closed and Open Structures in Detergent for the Influenza Virus Hemagglutinin Fusion Peptide and Correlation of Hydrophobic Surface Area with Fusion Catalysis. Journal of the American Chemical Society. 137(24). 7548–7551. 27 indexed citations

13.

Ghosh, Ujjayini, et al.. (2013). Detection of closed influenza virus hemagglutinin fusion peptide structures in membranes by backbone 13CO-15N rotational-echo double-resonance solid-state NMR. Journal of Biomolecular NMR. 55(2). 139–146. 19 indexed citations

14.

Ghosh, Ujjayini, et al.. (2012). Residue-specific membrane location of peptides and proteins using specifically and extensively deuterated lipids and 13C–2H rotational-echo double-resonance solid-state NMR. Journal of Biomolecular NMR. 55(1). 11–17. 11 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