Regina Pinto

697 total citations · 1 hit paper
7 papers, 550 citations indexed

About

Regina Pinto is a scholar working on Oncology, Cancer Research and Molecular Biology. According to data from OpenAlex, Regina Pinto has authored 7 papers receiving a total of 550 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Oncology, 4 papers in Cancer Research and 3 papers in Molecular Biology. Recurrent topics in Regina Pinto's work include Cancer Genomics and Diagnostics (4 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and COVID-19 and healthcare impacts (2 papers). Regina Pinto is often cited by papers focused on Cancer Genomics and Diagnostics (4 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and COVID-19 and healthcare impacts (2 papers). Regina Pinto collaborates with scholars based in Portugal, Spain and Italy. Regina Pinto's co-authors include Fernando Schmitt, Joana Paredes, José Cameselle‐Teijeiro, Sara Ricardo, Fernanda Milanezi, Dina Leitão, Renê Gerhard, André Filipe Vieira, António Polónia and Luı́s Cirnes and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Clinical Pathology and BioMed Research International.

In The Last Decade

Regina Pinto

6 papers receiving 543 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Breast cancer stem cell markers CD44, CD24 and ALDH1: expression distribution within intrinsic molecular subtype

2011 491 citations Sara Ricardo, André Filipe Vieira et al. Journal of Clinical Pathology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Regina Pinto Portugal	4	408	268	187	71	56	7	550
Irina Primac Belgium	10	260 0.6×	338 1.3×	229 1.2×	74 1.0×	56 1.0×	12	669
Agnieszka Martowicz Austria	14	277 0.7×	282 1.1×	157 0.8×	60 0.8×	97 1.7×	20	587
Julie Roques France	12	452 1.1×	352 1.3×	307 1.6×	54 0.8×	44 0.8×	17	748
Jorge Aguilar United States	3	421 1.0×	274 1.0×	170 0.9×	32 0.5×	43 0.8×	4	515
Aleksandra Markiewicz Poland	15	499 1.2×	287 1.1×	283 1.5×	124 1.7×	53 0.9×	33	714
Gemma Shay United States	9	320 0.8×	299 1.1×	242 1.3×	72 1.0×	44 0.8×	10	637
Janak Raval United States	2	396 1.0×	270 1.0×	157 0.8×	30 0.4×	40 0.7×	3	488
Saswati Karmakar United States	12	301 0.7×	467 1.7×	165 0.9×	86 1.2×	61 1.1×	20	692
Antje Andreas Germany	10	322 0.8×	212 0.8×	212 1.1×	86 1.2×	50 0.9×	16	533
Bianca D. Capaldo Australia	7	308 0.8×	344 1.3×	176 0.9×	74 1.0×	40 0.7×	9	577

Countries citing papers authored by Regina Pinto

Since Specialization

Citations

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

Fields of papers citing papers by Regina Pinto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Regina Pinto

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

All Works

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7 of 7 papers shown

1.

Pinto, Regina & Fernando Schmitt. (2023). A Real-World Study Reporting the Use of Foundation Medicine® Testing in Portugal. SHILAP Revista de lepidopterología. 4(3). 156–165.

2.

Pinto, Regina, et al.. (2022). Tissue management in precision medicine: What the pathologist needs to know in the molecular era. Frontiers in Molecular Biosciences. 9. 983102–983102. 7 indexed citations

3.

Ricardo, Sara, Diana Martins, Ana C. Magalhães, et al.. (2022). Searching for SARS-CoV-2 in Cancer Tissues: Results of an Extensive Methodologic Approach based on ACE2 and Furin Expression. Cancers. 14(11). 2582–2582. 2 indexed citations

4.

Pinto, Daniel, et al.. (2020). How the COVID‐19 Pandemic Impacted Oncological Molecular Diagnosis: A Picture from a National Reference Center for Molecular Pathology. BioMed Research International. 2020(1). 8397053–8397053. 3 indexed citations

5.

Gullo, Irene, Ana Marques, Regina Pinto, Luı́s Cirnes, & Fernando Schmitt. (2020). Morphological control for molecular testing: a practical approach. Journal of Clinical Pathology. 74(5). 331–333. 8 indexed citations

6.

Polónia, António, Regina Pinto, José Cameselle‐Teijeiro, Fernando Schmitt, & Joana Paredes. (2017). Prognostic value of stromal tumour infiltrating lymphocytes and programmed cell death-ligand 1 expression in breast cancer. Journal of Clinical Pathology. 70(10). 860–867. 39 indexed citations

7.

Ricardo, Sara, André Filipe Vieira, Renê Gerhard, et al.. (2011). Breast cancer stem cell markers CD44, CD24 and ALDH1: expression distribution within intrinsic molecular subtype. Journal of Clinical Pathology. 64(11). 937–946. 491 indexed citations breakdown →

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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