Vijayaraghavan Rangachari

797 total citations
34 papers, 567 citations indexed

About

Vijayaraghavan Rangachari is a scholar working on Molecular Biology, Physiology and Neurology. According to data from OpenAlex, Vijayaraghavan Rangachari has authored 34 papers receiving a total of 567 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 22 papers in Physiology and 8 papers in Neurology. Recurrent topics in Vijayaraghavan Rangachari's work include Alzheimer's disease research and treatments (22 papers), Protein Structure and Dynamics (9 papers) and Prion Diseases and Protein Misfolding (8 papers). Vijayaraghavan Rangachari is often cited by papers focused on Alzheimer's disease research and treatments (22 papers), Protein Structure and Dynamics (9 papers) and Prion Diseases and Protein Misfolding (8 papers). Vijayaraghavan Rangachari collaborates with scholars based in United States, Germany and Russia. Vijayaraghavan Rangachari's co-authors include Amit Kumar, Sarah E. Morgan, Preetam Ghosh, Vladimir N. Uversky, Dexter N. Dean, Ashwin Vaidya, Melissa A. Moss, Pradipta Das, Pratip Rana and Daniel F. Lyons and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Journal of Biological Chemistry.

In The Last Decade

Vijayaraghavan Rangachari

33 papers receiving 564 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vijayaraghavan Rangachari United States 16 383 279 93 79 53 34 567
Kalyani Sanagavarapu Sweden 6 301 0.8× 339 1.2× 58 0.6× 124 1.6× 54 1.0× 7 490
Vladimir Zamotin Sweden 10 469 1.2× 410 1.5× 54 0.6× 55 0.7× 34 0.6× 16 674
Yoav Atsmon‐Raz Israel 13 319 0.8× 242 0.9× 69 0.7× 191 2.4× 33 0.6× 23 520
Claudia Parrini Italy 7 513 1.3× 453 1.6× 84 0.9× 107 1.4× 60 1.1× 7 741
Tom Scheidt United Kingdom 10 299 0.8× 258 0.9× 38 0.4× 59 0.7× 55 1.0× 16 498
Ruitian Liu United States 10 269 0.7× 292 1.0× 52 0.6× 69 0.9× 77 1.5× 13 530
Suzana Aulić Italy 14 351 0.9× 135 0.5× 98 1.1× 25 0.3× 55 1.0× 24 618
Mohtadin Hashemi United States 12 314 0.8× 242 0.9× 50 0.5× 99 1.3× 53 1.0× 23 433
Hamed Shaykhalishahi Germany 13 258 0.7× 338 1.2× 235 2.5× 65 0.8× 30 0.6× 19 556
Silvia Torrassa Italy 12 463 1.2× 458 1.6× 38 0.4× 69 0.9× 31 0.6× 12 664

Countries citing papers authored by Vijayaraghavan Rangachari

Since Specialization
Citations

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

Fields of papers citing papers by Vijayaraghavan Rangachari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vijayaraghavan Rangachari

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

All Works

20 of 20 papers shown
1.
Clemons, Tristan D., et al.. (2025). De Novo Amyloid Peptide–Polymer Blends with Enhanced Mechanical and Biological Properties. ACS Applied Polymer Materials. 7(6). 3739–3751.
2.
Wang, Xianjun, et al.. (2023). Sugar distributions on gangliosides guide the formation and stability of amyloid-β oligomers. Biophysical Chemistry. 300. 107073–107073. 4 indexed citations
3.
Banerjee, Siddhartha, et al.. (2023). α-Synuclein emulsifies TDP-43 prion-like domain—RNA liquid droplets to promote heterotypic amyloid fibrils. Communications Biology. 6(1). 1227–1227. 16 indexed citations
4.
Rangachari, Vijayaraghavan. (2023). Biomolecular condensates – extant relics or evolving microcompartments?. Communications Biology. 6(1). 656–656. 16 indexed citations
5.
Bhatt, Nemil, et al.. (2022). Distinct neurotoxic TDP-43 fibril polymorphs are generated by heterotypic interactions with α-Synuclein. Journal of Biological Chemistry. 298(11). 102498–102498. 13 indexed citations
6.
Rangachari, Vijayaraghavan, et al.. (2021). αS Oligomers Generated from Interactions with a Polyunsaturated Fatty Acid and a Dopamine Metabolite Differentially Interact with Aβ to Enhance Neurotoxicity. ACS Chemical Neuroscience. 12(21). 4153–4161. 7 indexed citations
7.
Uversky, Vladimir N., et al.. (2020). Granulins modulate liquid–liquid phase separation and aggregation of the prion-like C-terminal domain of the neurodegeneration-associated protein TDP-43. Journal of Biological Chemistry. 295(8). 2506–2519. 30 indexed citations
8.
Uversky, Vladimir N., et al.. (2020). Disorder and cysteines in proteins: A design for orchestration of conformational see-saw and modulatory functions. Progress in molecular biology and translational science. 331–373. 32 indexed citations
9.
Das, Pradipta, et al.. (2020). Effects of Stereochemistry and Hydrogen Bonding on Glycopolymer–Amyloid-β Interactions. Biomacromolecules. 21(10). 4280–4293. 14 indexed citations
10.
Dean, Dexter N., et al.. (2019). Cysteine-rich granulin-3 rapidly promotes amyloid-β fibrils in both redox states. Biochemical Journal. 476(5). 859–873. 8 indexed citations
11.
Dean, Dexter N., et al.. (2018). Propagation of an Aβ Dodecamer Strain Involves a Three-Step Mechanism and a Key Intermediate. Biophysical Journal. 114(3). 539–549. 7 indexed citations
12.
Dean, Dexter N., Pradipta Das, Pratip Rana, et al.. (2017). Strain-specific Fibril Propagation by an Aβ Dodecamer. Scientific Reports. 7(1). 40787–40787. 33 indexed citations
13.
Das, Pradipta, Dexter N. Dean, Fei Liu, et al.. (2017). Aqueous RAFT Synthesis of Glycopolymers for Determination of Saccharide Structure and Concentration Effects on Amyloid β Aggregation. Biomacromolecules. 18(10). 3359–3366. 23 indexed citations
14.
Ghosh, Preetam, Ashwin Vaidya, Amit Kumar, & Vijayaraghavan Rangachari. (2016). Determination of critical nucleation number for a single nucleation amyloid-β aggregation model. Mathematical Biosciences. 273. 70–79. 30 indexed citations
15.
Dean, Dexter N., Amit Kumar, Kayla M. Pate, Melissa A. Moss, & Vijayaraghavan Rangachari. (2015). Self-Propagative Replication of Amyloid-β Oligomers in Alzheimer Disease. Biophysical Journal. 108(2). 66a–66a. 1 indexed citations
16.
Kumar, Amit, Kayla M. Pate, Melissa A. Moss, Dexter N. Dean, & Vijayaraghavan Rangachari. (2014). Self-Propagative Replication of Aβ Oligomers Suggests Potential Transmissibility in Alzheimer Disease. PLoS ONE. 9(11). e111492–e111492. 26 indexed citations
17.
Kumar, Amit, et al.. (2012). Specific Soluble Oligomers of Amyloid-β Peptide Undergo Replication and Form Non-fibrillar Aggregates in Interfacial Environments. Journal of Biological Chemistry. 287(25). 21253–21264. 35 indexed citations
18.
19.
Ghosh, Preetam, et al.. (2010). Dynamics of protofibril elongation and association involved in Aβ42 peptide aggregation in Alzheimer’s disease. BMC Bioinformatics. 11(S6). S24–S24. 49 indexed citations
20.

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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