Panchika Prangkio

1.1k total citations · 1 hit paper
21 papers, 953 citations indexed

About

Panchika Prangkio is a scholar working on Molecular Biology, Microbiology and Biomedical Engineering. According to data from OpenAlex, Panchika Prangkio has authored 21 papers receiving a total of 953 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 7 papers in Microbiology and 5 papers in Biomedical Engineering. Recurrent topics in Panchika Prangkio's work include Lipid Membrane Structure and Behavior (7 papers), Bacterial Infections and Vaccines (5 papers) and Alzheimer's disease research and treatments (4 papers). Panchika Prangkio is often cited by papers focused on Lipid Membrane Structure and Behavior (7 papers), Bacterial Infections and Vaccines (5 papers) and Alzheimer's disease research and treatments (4 papers). Panchika Prangkio collaborates with scholars based in Thailand, United States and Taiwan. Panchika Prangkio's co-authors include Michael Mayer, Jerry Yang, Erik C. Yusko, Jiali Li, Ryan Rollings, Sheereen Majd, Jay M. Johnson, David Sept, Ricardo Capone and Inderjeet Saluja and has published in prestigious journals such as ACS Nano, PLoS ONE and Nature Nanotechnology.

In The Last Decade

Panchika Prangkio

20 papers receiving 938 citations

Hit Papers

Controlling protein trans... 2011 2026 2016 2021 2011 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Panchika Prangkio Thailand 9 650 371 183 179 147 21 953
Erik C. Yusko United States 11 1.4k 2.2× 628 1.7× 414 2.3× 106 0.6× 321 2.2× 16 1.7k
David Rodríguez‐Larrea Spain 17 556 0.9× 814 2.2× 139 0.8× 67 0.4× 140 1.0× 27 1.3k
Rubèn Serral Gracià Germany 8 267 0.4× 475 1.3× 77 0.4× 77 0.4× 61 0.4× 10 818
Loredana Mereuta Romania 21 666 1.0× 515 1.4× 165 0.9× 25 0.1× 217 1.5× 41 930
L.E.Göran Eriksson Sweden 12 95 0.1× 365 1.0× 141 0.8× 95 0.5× 81 0.6× 20 782
Daniel Fologea United States 16 1.3k 1.9× 518 1.4× 474 2.6× 34 0.2× 365 2.5× 45 1.6k
Jiwook Shim United States 17 889 1.4× 635 1.7× 275 1.5× 17 0.1× 160 1.1× 35 1.3k
Alina Asandei Romania 21 929 1.4× 518 1.4× 223 1.2× 28 0.2× 312 2.1× 41 1.1k
Philip A. Gurnev United States 22 244 0.4× 748 2.0× 62 0.3× 91 0.5× 27 0.2× 44 1.2k
Hirotaka Sasaki Japan 12 380 0.6× 327 0.9× 99 0.5× 24 0.1× 26 0.2× 29 628

Countries citing papers authored by Panchika Prangkio

Since Specialization
Citations

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

Fields of papers citing papers by Panchika Prangkio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Panchika Prangkio

This figure shows the co-authorship network connecting the top 25 collaborators of Panchika Prangkio. A scholar is included among the top collaborators of Panchika Prangkio 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 Panchika Prangkio. Panchika Prangkio 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.
Daranarong, Donraporn, et al.. (2024). Biological Evaluation of LL‐37 Antimicrobial Peptide‐Loaded Biodegradable Barrier Membranes in Guided Bone Regeneration. Journal of Polymer Science. 63(4). 818–828.
3.
Daduang, Sakda, Sompong Klaynongsruang, Suwimol Taweechaisupapong, et al.. (2023). The synergistic action of silver nanoparticles and ceftazidime against antibiotic-resistant Burkholderia pseudomallei: A modifying treatment. Process Biochemistry. 136. 351–361. 4 indexed citations
4.
Suree, Nuttee, et al.. (2023). CD4+ T cell-targeting immunoliposomes for treatment of latent HIV reservoir. European Journal of Pharmaceutics and Biopharmaceutics. 195. 114166–114166. 3 indexed citations
5.
Prangkio, Panchika, et al.. (2021). Silk Fibroin-Coated Liposomes as Biomimetic Nanocarrier for Long-Term Release Delivery System in Cancer Therapy. Molecules. 26(16). 4936–4936. 16 indexed citations
6.
Prangkio, Panchika, et al.. (2021). AFM Study of Nanoscale Membrane Perturbation Induced by Antimicrobial Lipopeptide C14 KYR. Membranes. 11(7). 495–495. 7 indexed citations
7.
Prangkio, Panchika, et al.. (2021). Anti-Herpes Simplex Virus Efficacy of Silk Cocoon, Silkworm Pupa and Non-Sericin Extracts. Antibiotics. 10(12). 1553–1553. 6 indexed citations
8.
Suree, Nuttee, et al.. (2020). Drug Delivery System Targeting CD4+ T Cells for HIV-1 Latency Reactivation Towards the Viral Eradication. Journal of Pharmaceutical Sciences. 109(10). 3013–3020. 8 indexed citations
9.
Prangkio, Panchika, et al.. (2018). Structural requirement of the hydrophobic region of the Bordetella pertussis CyaA-hemolysin for functional association with CyaC-acyltransferase in toxin acylation. Biochemical and Biophysical Research Communications. 499(4). 862–867. 1 indexed citations
10.
Shank, Lalida, et al.. (2017). Zn 2+ -dependent autocatalytic activity of the Bordetella pertussis CyaA-hemolysin. Biochemical and Biophysical Research Communications. 485(4). 720–724. 1 indexed citations
12.
Kittiwachana, Sila, Puttinan Meepowpan, Nawee Kungwan, et al.. (2016). Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches. Journal of Computer-Aided Molecular Design. 30(6). 471–488. 3 indexed citations
13.
Liu, Haiyan, et al.. (2016). Benzothiazole Amphiphiles Ameliorate Amyloid β-Related Cell Toxicity and Oxidative Stress. ACS Chemical Neuroscience. 7(6). 682–688. 17 indexed citations
15.
Yusko, Erik C., Panchika Prangkio, David Sept, et al.. (2012). Single-Particle Characterization of Aβ Oligomers in Solution. ACS Nano. 6(7). 5909–5919. 104 indexed citations
16.
Prangkio, Panchika, Erik C. Yusko, David Sept, Jerry Yang, & Michael Mayer. (2012). Multivariate Analyses of Amyloid-Beta Oligomer Populations Indicate a Connection between Pore Formation and Cytotoxicity. PLoS ONE. 7(10). e47261–e47261. 73 indexed citations
17.
Prangkio, Panchika, et al.. (2011). Self-assembled, cation-selective ion channels from an oligo(ethylene glycol) derivative of benzothiazole aniline. Biochimica et Biophysica Acta (BBA) - Biomembranes. 1808(12). 2877–2885. 14 indexed citations
18.
Yusko, Erik C., Jay M. Johnson, Sheereen Majd, et al.. (2011). Controlling protein translocation through nanopores with bio-inspired fluid walls. Nature Nanotechnology. 6(4). 253–260. 561 indexed citations breakdown →
19.
Capone, Ricardo, Felipe García Quiroz, Panchika Prangkio, et al.. (2009). Amyloid-β Ion Channels in Artificial Lipid Bilayers and Neuronal Cells. Resolving a Controversy. Biophysical Journal. 96(3). 389a–389a. 2 indexed citations
20.
Capone, Ricardo, Felipe García Quiroz, Panchika Prangkio, et al.. (2009). Amyloid-β-Induced Ion Flux in Artificial Lipid Bilayers and Neuronal Cells: Resolving a Controversy. Neurotoxicity Research. 16(1). 1–13. 103 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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