Tânia Cova

1.3k total citations
46 papers, 958 citations indexed

About

Tânia Cova is a scholar working on Molecular Biology, Pharmaceutical Science and Computational Theory and Mathematics. According to data from OpenAlex, Tânia Cova has authored 46 papers receiving a total of 958 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 10 papers in Pharmaceutical Science and 7 papers in Computational Theory and Mathematics. Recurrent topics in Tânia Cova's work include RNA Interference and Gene Delivery (7 papers), Advancements in Transdermal Drug Delivery (7 papers) and Computational Drug Discovery Methods (7 papers). Tânia Cova is often cited by papers focused on RNA Interference and Gene Delivery (7 papers), Advancements in Transdermal Drug Delivery (7 papers) and Computational Drug Discovery Methods (7 papers). Tânia Cova collaborates with scholars based in Portugal, Spain and Italy. Tânia Cova's co-authors include Alberto A. C. C. Pais, Sandra C. C. Nunes, Carla Vitorino, Artur J. M. Valente, Dina Murtinho, João Sousa, João Basso, Maria Mendes, Ana Miranda and Victoria L. M. Herrera and has published in prestigious journals such as The Journal of Chemical Physics, Macromolecules and Journal of Agricultural and Food Chemistry.

In The Last Decade

Tânia Cova

44 papers receiving 944 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tânia Cova Portugal 18 342 215 207 161 156 46 958
Vito Foderà Denmark 24 929 2.7× 397 1.8× 167 0.8× 254 1.6× 110 0.7× 76 1.7k
Shuling Yu China 17 144 0.4× 215 1.0× 194 0.9× 176 1.1× 41 0.3× 44 726
Huihui Yuan China 21 452 1.3× 183 0.9× 216 1.0× 350 2.2× 86 0.6× 61 1.5k
Vijaykumar Sutariya United States 17 368 1.1× 283 1.3× 148 0.7× 132 0.8× 313 2.0× 48 1.1k
Lijiang Chen China 17 239 0.7× 116 0.5× 122 0.6× 171 1.1× 98 0.6× 53 775
Barnali Maiti India 25 486 1.4× 304 1.4× 286 1.4× 119 0.7× 246 1.6× 87 2.1k
Salar Hemmati Iran 19 302 0.9× 181 0.8× 177 0.9× 347 2.2× 64 0.4× 85 1.1k
Toshinori Shimanouchi Japan 26 1.1k 3.2× 303 1.4× 500 2.4× 208 1.3× 90 0.6× 140 1.9k

Countries citing papers authored by Tânia Cova

Since Specialization
Citations

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

Fields of papers citing papers by Tânia Cova

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tânia Cova

This figure shows the co-authorship network connecting the top 25 collaborators of Tânia Cova. A scholar is included among the top collaborators of Tânia Cova 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 Tânia Cova. Tânia Cova 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.
2.
Cova, Tânia, et al.. (2025). Prediction of Pt, Ir, Ru, and Rh complexes light absorption in the therapeutic window for phototherapy using machine learning. Journal of Cheminformatics. 17(1). 1–1. 2 indexed citations
3.
Mendes, Maria, Sandra C. C. Nunes, Tânia Cova, et al.. (2024). Charge-switchable cell-penetrating peptides for rerouting nanoparticles to glioblastoma treatment. Colloids and Surfaces B Biointerfaces. 241. 113983–113983. 10 indexed citations
4.
Cova, Tânia, et al.. (2024). Machine Learning-Based Prediction of Reduction Potentials for PtIV Complexes. Journal of Chemical Information and Modeling. 64(9). 3733–3743. 2 indexed citations
5.
Basso, João, Maria Mendes, Tânia Cova, et al.. (2022). A Stepwise Framework for the Systematic Development of Lipid Nanoparticles. Biomolecules. 12(2). 223–223. 23 indexed citations
6.
Cova, Tânia, Carla Vitorino, Márcio Ferreira, et al.. (2021). Artificial Intelligence and Quantum Computing as the Next Pharma Disruptors. Methods in molecular biology. 2390. 321–347. 15 indexed citations
7.
Lã, Filipa M.B., et al.. (2021). Female Voice-Related Sexual Attractiveness to Males: Does it Vary With Different Degrees of Conception Likelihood?. Journal of Voice. 37(3). 467.e19–467.e31.
8.
Mendes, Maria, João Basso, Jessica Silva-Fisher, et al.. (2020). Biomimeting ultra-small lipid nanoconstructs for glioblastoma treatment: A computationally guided experimental approach. International Journal of Pharmaceutics. 587. 119661–119661. 26 indexed citations
9.
Basso, João, Maria Mendes, Jéssica Silva, et al.. (2020). Sorting hidden patterns in nanoparticle performance for glioblastoma using machine learning algorithms. International Journal of Pharmaceutics. 592. 120095–120095. 16 indexed citations
10.
Miranda, Margarida, et al.. (2020). Diving into Batch-to-Batch Variability of Topical Products-a Regulatory Bottleneck. Pharmaceutical Research. 37(11). 218–218. 13 indexed citations
11.
Basso, João, Maria Mendes, Jessica Silva-Fisher, et al.. (2020). Peptide-lipid nanoconstructs act site-specifically towards glioblastoma growth impairment. European Journal of Pharmaceutics and Biopharmaceutics. 155. 177–189. 28 indexed citations
12.
Alagia, Adele, Andreia F. Jorge, Anna Aviñó, et al.. (2018). Exploring PAZ/3′-overhang interaction to improve siRNA specificity. A combined experimental and modeling study. Chemical Science. 9(8). 2074–2086. 25 indexed citations
13.
Basso, João, Maria Mendes, Tânia Cova, et al.. (2018). Analytical Quality by Design (AQbD) as a multiaddressable platform for co-encapsulating drug assays. Analytical Methods. 10(47). 5659–5671. 27 indexed citations
14.
Cova, Tânia, Bruce F. Milne, & Alberto A. C. C. Pais. (2018). Host flexibility and space filling in supramolecular complexation of cyclodextrins: A free-energy-oriented approach. Carbohydrate Polymers. 205. 42–54. 18 indexed citations
15.
Cova, Tânia, Dina Murtinho, Alberto A. C. C. Pais, & Artur J. M. Valente. (2018). Combining Cellulose and Cyclodextrins: Fascinating Designs for Materials and Pharmaceutics. Frontiers in Chemistry. 6. 271–271. 62 indexed citations
16.
Silva, Jéssica, Maria Mendes, Tânia Cova, et al.. (2018). Unstructured Formulation Data Analysis for the Optimization of Lipid Nanoparticle Drug Delivery Vehicles. AAPS PharmSciTech. 19(5). 2383–2394. 9 indexed citations
17.
Cova, Tânia, Alberto A. C. C. Pais, & J. Sérgio Seixas de Melo. (2017). Reconstructing the historical synthesis of mauveine from Perkin and Caro: procedure and details. Scientific Reports. 7(1). 6806–6806. 17 indexed citations
18.
Cova, Tânia, Sandra C. C. Nunes, Teresa M. V. D. Pinho e Melo, & Alberto A. C. C. Pais. (2017). Bambusurils as effective ion caging agents: Does desolvation guide conformation?. Chemical Physics Letters. 672. 89–96. 9 indexed citations
19.
Cova, Tânia, Sérgio M.C. Silva, Rita Oliveira, et al.. (2015). Novel serine-based gemini surfactants as chemical permeation enhancers of local anesthetics: A comprehensive study on structure–activity relationships, molecular dynamics and dermal delivery. European Journal of Pharmaceutics and Biopharmaceutics. 93. 205–213. 18 indexed citations
20.
Cova, Tânia, Sérgio M.C. Silva, Rita Oliveira, et al.. (2014). Lysine-based surfactants as chemical permeation enhancers for dermal delivery of local anesthetics. International Journal of Pharmaceutics. 474(1-2). 212–222. 17 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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