Nádia Pinto

1.5k total citations
58 papers, 868 citations indexed

About

Nádia Pinto is a scholar working on Genetics, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Nádia Pinto has authored 58 papers receiving a total of 868 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Genetics, 24 papers in Molecular Biology and 6 papers in Cognitive Neuroscience. Recurrent topics in Nádia Pinto's work include Forensic and Genetic Research (33 papers), Genetic Associations and Epidemiology (16 papers) and Molecular Biology Techniques and Applications (14 papers). Nádia Pinto is often cited by papers focused on Forensic and Genetic Research (33 papers), Genetic Associations and Epidemiology (16 papers) and Molecular Biology Techniques and Applications (14 papers). Nádia Pinto collaborates with scholars based in Portugal, Brazil and Spain. Nádia Pinto's co-authors include António Amorim, Leonor Gusmão, Ángel Carracedo, Rui Pereira, Carla Santos, Christopher Phillips, Sidney Emanuel Batista dos Santos, Roberto Hornero, Jesús Poza and Carlos Gómez and has published in prestigious journals such as Nucleic Acids Research, PLoS ONE and Scientific Reports.

In The Last Decade

Nádia Pinto

51 papers receiving 844 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nádia Pinto Portugal 15 561 351 108 79 50 58 868
Adele A. Mitchell United States 14 415 0.7× 303 0.9× 36 0.3× 31 0.4× 9 0.2× 20 777
Leonardo Arbiza Spain 17 491 0.9× 564 1.6× 12 0.1× 30 0.4× 21 0.4× 22 975
Francisco M. De La Vega United States 14 437 0.8× 401 1.1× 13 0.1× 35 0.4× 7 0.1× 21 828
Simone Rubinacci Switzerland 10 369 0.7× 180 0.5× 6 0.1× 20 0.3× 31 0.6× 22 512
Geoffrey B. Nilsen United States 5 982 1.8× 694 2.0× 18 0.2× 19 0.2× 5 0.1× 5 1.5k
Chiara Turchi Italy 16 479 0.9× 329 0.9× 15 0.1× 65 0.8× 97 1.9× 51 643
Xuanyao Liu Singapore 12 629 1.1× 478 1.4× 28 0.3× 5 0.1× 9 0.2× 20 935
Michael Wittig Germany 15 504 0.9× 670 1.9× 26 0.2× 59 0.7× 11 0.2× 28 1.2k
Marie Forest Canada 6 249 0.4× 150 0.4× 18 0.2× 14 0.2× 13 0.3× 8 375
Arianna Consiglio Italy 17 34 0.1× 359 1.0× 15 0.1× 56 0.7× 12 0.2× 36 696

Countries citing papers authored by Nádia Pinto

Since Specialization
Citations

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

Fields of papers citing papers by Nádia Pinto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nádia Pinto

This figure shows the co-authorship network connecting the top 25 collaborators of Nádia Pinto. A scholar is included among the top collaborators of Nádia Pinto 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 Nádia Pinto. Nádia Pinto 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.
Hornero, Roberto, et al.. (2025). Effect of MAPT gene variations on the brain electrical activity: A multiplex network study. Biomedical Signal Processing and Control. 110. 108129–108129.
2.
Amorim, António, et al.. (2025). The impact of parameter variation in the quantification of forensic genetic evidence. Scientific Reports. 15(1). 2524–2524. 1 indexed citations
3.
4.
5.
Pinto, Nádia, et al.. (2023). The sequence of the repetitive motif influences the frequency of multistep mutations in Short Tandem Repeats. Scientific Reports. 13(1). 10251–10251. 3 indexed citations
6.
Martins, Sandra, Alexandra M. Lopes, Nádia Pinto, et al.. (2023). Non-coding variants in VAMP2 and SNAP25 affect gene expression: potential implications in migraine susceptibility. The Journal of Headache and Pain. 24(1). 78–78.
7.
Amorim, António, et al.. (2022). Quantification of forensic genetic evidence: Comparison of results obtained by qualitative and quantitative software for real casework samples. Forensic Science International Genetics. 59. 102715–102715. 6 indexed citations
8.
Macedo, Ana, Carlos Gómez, Jesús Poza, et al.. (2021). Risk Variants in Three Alzheimer’s Disease Genes Show Association with EEG Endophenotypes. Journal of Alzheimer s Disease. 80(1). 209–223. 5 indexed citations
9.
Pinto, Nádia, Ricardo Simões, António Amorim, & Eduardo Conde‐Sousa. (2019). Optimizing the information increase through the addition of relatives and genetic markers in identification and kinship cases. Forensic Science International Genetics. 40. 210–218. 10 indexed citations
10.
Catanesi, Cecilia Inés, et al.. (2019). X-chromosome data for 12 STRs: Towards an Argentinian database of forensic haplotype frequencies. Forensic Science International Genetics. 41. e8–e13. 18 indexed citations
11.
Arenas, Miguel, Filipe Pereira, Manuela Oliveira, et al.. (2017). Forensic genetics and genomics: Much more than just a human affair. PLoS Genetics. 13(9). e1006960–e1006960. 57 indexed citations
12.
Conde‐Sousa, Eduardo, et al.. (2017). Key individuals for discerning pedigrees belonging to the same autosomal kinship class. Forensic Science International Genetics. 29. 71–79. 6 indexed citations
13.
Amorim, António, Manuel Crespillo, J. A. Luque, et al.. (2016). Formulation and communication of evaluative forensic science expert opinion—A GHEP-ISFG contribution to the establishment of standards. Forensic Science International Genetics. 25. 210–213. 6 indexed citations
14.
Coble, Michael D., John Buckleton, John M. Butler, et al.. (2016). DNA Commission of the International Society for Forensic Genetics: Recommendations on the validation of software programs performing biostatistical calculations for forensic genetics applications. Forensic Science International Genetics. 25. 191–197. 66 indexed citations
15.
Pinto, Nádia, Leonor Gusmão, & António Amorim. (2013). Mutation and mutation rates at Y chromosome specific Short Tandem Repeat Polymorphisms (STRs): A reappraisal. Forensic Science International Genetics. 9. 20–24. 12 indexed citations
16.
Pinto, Nádia, Eduardo Conde‐Sousa, Rui Pereira, et al.. (2012). Assessing paternities with inconclusive STR results: The suitability of bi-allelic markers. Forensic Science International Genetics. 7(1). 16–21. 22 indexed citations
17.
Pereira, Rui, Christopher Phillips, Nádia Pinto, et al.. (2012). Straightforward Inference of Ancestry and Admixture Proportions through Ancestry-Informative Insertion Deletion Multiplexing. PLoS ONE. 7(1). e29684–e29684. 186 indexed citations
18.
Pinto, Nádia, Pedro V. Silva, & António Amorim. (2011). A general method to assess the utility of the X-chromosomal markers in kinship testing. Forensic Science International Genetics. 6(2). 198–207. 21 indexed citations
19.
Pinto, Nádia, Pedro V. Silva, & António Amorim. (2010). General Derivation of the Sets of Pedigrees with the Same Kinship Coefficients. Human Heredity. 70(3). 194–204. 15 indexed citations
20.
Gomes, Iva, Vânia Pereira, Verónica Gomes, et al.. (2008). The Karimojong from Uganda: Genetic characterization using an X-STR decaplex system. Forensic Science International Genetics. 3(4). e127–e128. 18 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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