Dulce Quelhas

1.9k total citations
51 papers, 1.0k citations indexed

About

Dulce Quelhas is a scholar working on Molecular Biology, Physiology and Clinical Biochemistry. According to data from OpenAlex, Dulce Quelhas has authored 51 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 14 papers in Physiology and 10 papers in Clinical Biochemistry. Recurrent topics in Dulce Quelhas's work include Glycosylation and Glycoproteins Research (14 papers), Metabolism and Genetic Disorders (10 papers) and Lysosomal Storage Disorders Research (8 papers). Dulce Quelhas is often cited by papers focused on Glycosylation and Glycoproteins Research (14 papers), Metabolism and Genetic Disorders (10 papers) and Lysosomal Storage Disorders Research (8 papers). Dulce Quelhas collaborates with scholars based in Portugal, Belgium and Netherlands. Dulce Quelhas's co-authors include J. A. Tenreiro Machado, Gert Matthijs, Jaak Jaeken, François Foulquier, Wim Annaert, Elisa Leão Teles, Els Schollen, Laura Vilarinho, Philippa B. Mills and Willy Morelle and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Dulce Quelhas

46 papers receiving 990 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dulce Quelhas Portugal 18 706 242 209 149 146 51 1.0k
Laura Llacuna Spain 14 701 1.0× 166 0.7× 97 0.5× 38 0.3× 47 0.3× 16 1.2k
Rency S. Varghese United States 23 1.4k 1.9× 70 0.3× 99 0.5× 40 0.3× 88 0.6× 66 1.8k
Barbara Chaneton United Kingdom 7 1.5k 2.1× 241 1.0× 80 0.4× 40 0.3× 17 0.1× 7 1.9k
Eunsook S. Jin United States 20 1.5k 2.1× 378 1.6× 97 0.5× 157 1.1× 11 0.1× 37 2.2k
Kazuki Ohno Japan 25 496 0.7× 618 2.6× 178 0.9× 17 0.1× 384 2.6× 57 1.2k
Chao-Yuh Yang United States 17 354 0.5× 129 0.5× 108 0.5× 41 0.3× 18 0.1× 29 924
Chenggong Zong United States 23 1.3k 1.8× 149 0.6× 324 1.6× 65 0.4× 15 0.1× 37 1.6k
Vidya Venkatraman United States 20 670 0.9× 137 0.6× 99 0.5× 23 0.2× 13 0.1× 37 1.1k
Torsten Ehrig United States 13 657 0.9× 65 0.3× 182 0.9× 35 0.2× 24 0.2× 25 1.2k

Countries citing papers authored by Dulce Quelhas

Since Specialization
Citations

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

Fields of papers citing papers by Dulce Quelhas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dulce Quelhas

This figure shows the co-authorship network connecting the top 25 collaborators of Dulce Quelhas. A scholar is included among the top collaborators of Dulce Quelhas 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 Dulce Quelhas. Dulce Quelhas 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.
Azevedo, Luı́sa, et al.. (2025). A comprehensive update of genotype–phenotype correlations in PMM2-CDG: insights from molecular and structural analyses. Orphanet Journal of Rare Diseases. 20(1). 207–207.
2.
Monfregola, Jlenia, Isaura Ribeiro, Luciana Moreira, et al.. (2024). Investigating p.Ala1035Val in NPC1: New Cellular Models for Niemann–Pick Type C Disease. International Journal of Molecular Sciences. 25(22). 12186–12186.
3.
Quelhas, Dulce & Jaak Jaeken. (2024). Treatment of congenital disorders of glycosylation: An overview. Molecular Genetics and Metabolism. 143(1-2). 108567–108567. 6 indexed citations
4.
Nogueira, Célia, et al.. (2023). Diagnosis across a cohort of “atypical” atypical and complex parkinsonism. Parkinsonism & Related Disorders. 111. 105408–105408. 1 indexed citations
5.
Encarnação, Marisa, et al.. (2023). Challenges in the Definitive Diagnosis of Niemann–Pick Type C—Leaky Variants and Alternative Transcripts. Genes. 14(11). 1990–1990. 1 indexed citations
6.
Silva, Jorge Diogo Da, Márcio Cardoso, Cristina Garrido, et al.. (2023). Diagnostic accuracy and the first genotype–phenotype correlation in glycogen storage disease type V. Pediatric Research. 96(2). 365–371. 2 indexed citations
7.
Martins, Esmeralda, et al.. (2022). Glutaric Aciduria Type 2 Presenting in Adult Life With Hypoglycemia and Encephalopathic Hyperammonemia. Journal of Medical Cases. 13(2). 56–60. 3 indexed citations
8.
Čechová, Anna, Tomáš Honzík, Andrew C. Edmondson, et al.. (2021). Should patients with Phosphomannomutase 2-CDG (PMM2-CDG) be screened for adrenal insufficiency?. Molecular Genetics and Metabolism. 133(4). 397–399. 6 indexed citations
9.
Encarnação, Marisa, Maria Francisca Coutinho, Isaura Ribeiro, et al.. (2020). NPC1 silent variant induces skipping of exon 11 (p.V562V) and unfolded protein response was found in a specific Niemann‐Pick type C patient. Molecular Genetics & Genomic Medicine. 8(11). e1451–e1451. 12 indexed citations
10.
Laranjeira, Francisco, et al.. (2019). Genotype‐phenotype correlations and BH4 estimated responsiveness in patients with phenylketonuria from Rio de Janeiro, Southeast Brazil. Molecular Genetics & Genomic Medicine. 7(5). e610–e610. 8 indexed citations
11.
Laranjeira, Francisco, et al.. (2018). Mutation analysis of the PAH gene in phenylketonuria patients from Rio de Janeiro, Southeast Brazil. Molecular Genetics & Genomic Medicine. 6(4). 575–591. 13 indexed citations
12.
Ferdinandusse, Sacha, Liesbeth Keldermans, Dulce Quelhas, et al.. (2017). Galactose Epimerase Deficiency: Expanding the Phenotype. JIMD Reports. 37. 19–25. 6 indexed citations
13.
Quelhas, Dulce, et al.. (2016). Exuberant myopathic phenotype in a DPAGT1-CDG patient. Journal of Inherited Metabolic Disease. 139.
14.
Rocha, Júlio César, Francjan J. van Spronsen, Manuela Almeida, et al.. (2012). Dietary treatment in phenylketonuria does not lead to increased risk of obesity or metabolic syndrome. Molecular Genetics and Metabolism. 107(4). 659–663. 78 indexed citations
15.
Machado, J. A. Tenreiro, et al.. (2011). Entropy analysis of the DNA code dynamics in human chromosomes. Computers & Mathematics with Applications. 62(3). 1612–1617. 20 indexed citations
16.
Machado, J. A. Tenreiro, et al.. (2011). Wavelet analysis of human DNA. Genomics. 98(3). 155–163. 28 indexed citations
17.
Amaral, Cristina, et al.. (2010). Quantitative analysis of five sterols in amniotic fluid by GC–MS: Application to the diagnosis of cholesterol biosynthesis defects. Journal of Chromatography B. 878(23). 2130–2136. 18 indexed citations
18.
Duarte, José Alberto, Anderson H.F.F. Leão, José Magalhães, et al.. (2004). Strenuous exercise aggravates MDMA-induced skeletal muscle damage in mice. Toxicology. 206(3). 349–358. 19 indexed citations
19.
20.
Jorge, Paula, Dulce Quelhas, Pedro Oliveira, Rui Pinto, & António Nogueira. (1994). X-linked adrenoleukodystrophy in patients with idiopathic addison disease. European Journal of Pediatrics. 153(8). 594–597. 25 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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