Kadi-Liis Veiman

607 total citations
10 papers, 445 citations indexed

About

Kadi-Liis Veiman is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Kadi-Liis Veiman has authored 10 papers receiving a total of 445 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 4 papers in Genetics and 2 papers in Cancer Research. Recurrent topics in Kadi-Liis Veiman's work include RNA Interference and Gene Delivery (9 papers), Advanced biosensing and bioanalysis techniques (8 papers) and Virus-based gene therapy research (4 papers). Kadi-Liis Veiman is often cited by papers focused on RNA Interference and Gene Delivery (9 papers), Advanced biosensing and bioanalysis techniques (8 papers) and Virus-based gene therapy research (4 papers). Kadi-Liis Veiman collaborates with scholars based in Estonia, Sweden and France. Kadi-Liis Veiman's co-authors include Ülo Langel, Kaido Kurrikoff, Tõnis Lehto, Kadri Künnapuu, Piret Arukuusk, Christophe Chassaing, Alice Gaudin, Kalle Pärn, J. Richard and Margus Pooga and has published in prestigious journals such as Scientific Reports, International Journal of Molecular Sciences and Journal of Controlled Release.

In The Last Decade

Kadi-Liis Veiman

10 papers receiving 439 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kadi-Liis Veiman Estonia	9	348	92	74	63	46	10	445
Pedro M. D. Moreno Sweden	16	636 1.8×	72 0.8×	35 0.5×	99 1.6×	44 1.0×	32	718
Eman M. Zaghloul Sweden	15	534 1.5×	66 0.7×	42 0.6×	100 1.6×	28 0.6×	25	657
Ko Tanaka Japan	8	291 0.8×	124 1.3×	56 0.8×	47 0.7×	38 0.8×	9	373
Ivana Ruseska Austria	4	311 0.9×	53 0.6×	33 0.4×	42 0.7×	19 0.4×	10	388
Nicholas Flynn United States	12	279 0.8×	79 0.9×	62 0.8×	50 0.8×	11 0.2×	17	422
Marina Buyanova United States	9	413 1.2×	81 0.9×	79 1.1×	42 0.7×	18 0.4×	11	519
Irene Martín Germany	10	551 1.6×	82 0.9×	25 0.3×	101 1.6×	34 0.7×	10	584
Tõnis Lehto Sweden	10	332 1.0×	53 0.6×	42 0.6×	62 1.0×	24 0.5×	13	389
Atieh Hashemi Iran	13	311 0.9×	65 0.7×	64 0.9×	48 0.8×	64 1.4×	44	473
Kristina Najjar United States	8	492 1.4×	62 0.7×	50 0.7×	89 1.4×	13 0.3×	10	553

Countries citing papers authored by Kadi-Liis Veiman

Since Specialization

Citations

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

Fields of papers citing papers by Kadi-Liis Veiman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kadi-Liis Veiman. 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 Kadi-Liis Veiman. The network helps show where Kadi-Liis Veiman may publish in the future.

Co-authorship network of co-authors of Kadi-Liis Veiman

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

All Works

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10 of 10 papers shown

Veiman, Kadi-Liis, et al.. (2021). Opportunities and Pitfalls of Fluorescent Labeling Methodologies for Extracellular Vesicle Profiling on High-Resolution Single-Particle Platforms. International Journal of Molecular Sciences. 22(19). 10510–10510. 42 indexed citations

Gaudin, Alice, et al.. (2020). Challenges and Opportunities in the Delivery of Cancer Therapeutics: Update on Recent Progress. Therapeutic Delivery. 12(1). 55–76. 81 indexed citations

Kurrikoff, Kaido, et al.. (2019). Effective lung-targeted RNAi in mice with peptide-based delivery of nucleic acid. Scientific Reports. 9(1). 19926–19926. 20 indexed citations

Künnapuu, Kadri, et al.. (2018). Tumor gene therapy by systemic delivery of plasmid DNA with cell‐penetrating peptides. FASEB BioAdvances. 1(2). 105–114. 24 indexed citations

Kurrikoff, Kaido, Kadi-Liis Veiman, Kadri Künnapuu, et al.. (2017). Effective in vivo gene delivery with reduced toxicity, achieved by charge and fatty acid -modified cell penetrating peptide. Scientific Reports. 7(1). 17056–17056. 39 indexed citations

Arukuusk, Piret, Kaido Kurrikoff, Daniel Vasconcelos, et al.. (2016). Optimization of in vivo DNA delivery with NickFect peptide vectors. Journal of Controlled Release. 241. 135–143. 42 indexed citations

Veiman, Kadi-Liis, Kadri Künnapuu, Tõnis Lehto, et al.. (2015). PEG shielded MMP sensitive CPPs for efficient and tumor specific gene delivery in vivo. Journal of Controlled Release. 209. 238–247. 101 indexed citations

Kurrikoff, Kaido, Kadi-Liis Veiman, & Ülo Langel. (2015). CPP-Based Delivery System for In Vivo Gene Delivery. Methods in molecular biology. 1324. 339–347. 3 indexed citations

Regberg, Jakob, Mattias Hällbrink, Kaido Kurrikoff, et al.. (2013). Peptide-Based Delivery of Oligonucleotides Across Blood–Brain Barrier Model. International Journal of Peptide Research and Therapeutics. 20(2). 169–178. 15 indexed citations

10.

Veiman, Kadi-Liis, Imre Mäger, Kariem Ezzat, et al.. (2012). PepFect14 Peptide Vector for Efficient Gene Delivery in Cell Cultures. Molecular Pharmaceutics. 10(1). 199–210. 78 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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