Óscar Tapia

1.1k total citations
25 papers, 743 citations indexed

About

Óscar Tapia is a scholar working on Molecular Biology, Surgery and Pathology and Forensic Medicine. According to data from OpenAlex, Óscar Tapia has authored 25 papers receiving a total of 743 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 11 papers in Surgery and 6 papers in Pathology and Forensic Medicine. Recurrent topics in Óscar Tapia's work include Cholangiocarcinoma and Gallbladder Cancer Studies (11 papers), PI3K/AKT/mTOR signaling in cancer (5 papers) and Cancer-related gene regulation (4 papers). Óscar Tapia is often cited by papers focused on Cholangiocarcinoma and Gallbladder Cancer Studies (11 papers), PI3K/AKT/mTOR signaling in cancer (5 papers) and Cancer-related gene regulation (4 papers). Óscar Tapia collaborates with scholars based in Chile, United States and Türkiye. Óscar Tapia's co-authors include Juan Carlos Roa, Alejandra Sandoval, Pamela Leal, Pablo Letelier, Ismael Riquelme, Juan Carlos Araya, Patricia García, Kurt Buchegger, Helga Weber and Miguel Villaseca and has published in prestigious journals such as Journal of Clinical Oncology, Gastroenterology and PLoS ONE.

In The Last Decade

Óscar Tapia

20 papers receiving 732 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Óscar Tapia Chile 15 401 310 241 209 176 25 743
Liuxin Cai China 10 381 1.0× 146 0.5× 208 0.9× 205 1.0× 157 0.9× 18 712
Annapurna Gupta India 10 187 0.5× 248 0.8× 152 0.6× 133 0.6× 118 0.7× 16 469
Victoria Valinluck Lao United States 9 510 1.3× 86 0.3× 288 1.2× 237 1.1× 94 0.5× 17 797
Jueping Song United States 13 770 1.9× 154 0.5× 124 0.5× 535 2.6× 91 0.5× 20 1.0k
Jinwang Wei China 14 446 1.1× 105 0.3× 219 0.9× 405 1.9× 105 0.6× 21 783
Helga Weber Chile 13 343 0.9× 117 0.4× 150 0.6× 119 0.6× 85 0.5× 28 562
Paula Olaizola Spain 9 369 0.9× 190 0.6× 118 0.5× 163 0.8× 68 0.4× 15 690
Shunli Shen China 16 349 0.9× 135 0.4× 187 0.8× 249 1.2× 61 0.3× 32 689
Francesca Duraturo Italy 17 341 0.9× 86 0.3× 334 1.4× 313 1.5× 68 0.4× 37 794
Wen‐Long Guan China 12 226 0.6× 204 0.7× 400 1.7× 189 0.9× 309 1.8× 27 816

Countries citing papers authored by Óscar Tapia

Since Specialization
Citations

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

Fields of papers citing papers by Óscar Tapia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Óscar Tapia

This figure shows the co-authorship network connecting the top 25 collaborators of Óscar Tapia. A scholar is included among the top collaborators of Óscar Tapia 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 Óscar Tapia. Óscar Tapia 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.
Taşkın, Orhun Çığ, Olca Baştürk, Michelle D. Reid, et al.. (2020). Gallbladder polyps: Correlation of size and clinicopathologic characteristics based on updated definitions. PLoS ONE. 15(9). e0237979–e0237979. 30 indexed citations
2.
Tapia, Óscar, et al.. (2020). Accidentalidad de la población trabajadora ecuatoriana: análisis de variables para su calificación. 4(1). 22–31.
3.
Riquelme, Ismael, Óscar Tapia, Jaime A. Espinoza, et al.. (2016). The Gene Expression Status of the PI3K/AKT/mTOR Pathway in Gastric Cancer Tissues and Cell Lines. Pathology & Oncology Research. 22(4). 797–805. 82 indexed citations
4.
Roa, Juan Carlos, Juan Carlos Araya, Enrique Bellolio, et al.. (2016). Poorly cohesive cell (diffuse-infiltrative/signet ring cell) carcinomas of the gallbladder: clinicopathological analysis of 24 cases identified in 628 gallbladder carcinomas. Human Pathology. 60. 24–31. 7 indexed citations
5.
Tapia, Óscar. (2016). Tumor glómico gástrico: presentación de un caso. Revista Chilena de Cirugía. 68(5). 341–342.
6.
Riquelme, Ismael, Óscar Tapia, Pamela Leal, et al.. (2015). miR-101-2, miR-125b-2 and miR-451a act as potential tumor suppressors in gastric cancer through regulation of the PI3K/AKT/mTOR pathway. Cellular Oncology. 39(1). 23–33. 105 indexed citations
7.
Ili, Carmen, Priscilla Brebi, Patricia García, et al.. (2015). Effects of c-FLIPL Knockdown in Cervical Uterine Carcinoma Cell Lines. International Journal of Morphology. 33(2). 638–646.
8.
9.
Tapia, Óscar, Ismael Riquelme, Pamela Leal, et al.. (2014). The PI3K/AKT/mTOR pathway is activated in gastric cancer with potential prognostic and predictive significance. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 465(1). 25–33. 160 indexed citations
10.
Riquelme, Ismael, Óscar Tapia, Alejandra Sandoval, et al.. (2014). Mo1659 The PI3K/AKT/mTOR Pathway in Gastric Cancer and Its Potential Relationship With Mir-125b, Mir-451 and Mir-101. Gastroenterology. 146(5). S–629. 1 indexed citations
11.
Ili, Carmen, Priscilla Brebi, Óscar Tapia, et al.. (2013). Cellular FLICE-like Inhibitory Protein Long Form (c-FLIPL) Overexpression is Related to Cervical Cancer Progression. International Journal of Gynecological Pathology. 32(3). 316–322. 14 indexed citations
12.
Roa, Juan Carlos, et al.. (2013). AKT/mTOR substrate P70S6K is frequently phosphorylated in gallbladder cancer tissue and cell lines. OncoTargets and Therapy. 6. 1373–1373. 21 indexed citations
13.
Letelier, Pablo, Patricia García, Pamela Leal, et al.. (2013). Immunohistochemical Expression of Vascular Endothelial Growth Factor A in Advanced Gallbladder Carcinoma. Applied immunohistochemistry & molecular morphology. 22(7). 530–536. 29 indexed citations
14.
15.
Roa, Juan Carlos, Óscar Tapia, Carlos Manterola, et al.. (2013). Early gallbladder carcinoma has a favorable outcome but Rokitansky–Aschoff sinus involvement is an adverse prognostic factor. Archiv für Pathologische Anatomie und Physiologie und für Klinische Medicin. 463(5). 651–661. 25 indexed citations
16.
Letelier, Pablo, Priscilla Brebi, Óscar Tapia, & Juan Carlos Roa. (2012). DNA promoter methylation as a diagnostic and therapeutic biomarker in gallbladder cancer. Clinical Epigenetics. 4(1). 11–11. 25 indexed citations
17.
Tapia, Óscar. (2011). La dimensión centro-periferia en los partidos nacionalistas de Cataluña y el País Vasco 1977-2008. Dialnet (Universidad de la Rioja). 1 indexed citations
18.
Roa, Juan Carlos, Óscar Tapia, Aslı Çakır, et al.. (2011). Squamous cell and adenosquamous carcinomas of the gallbladder: clinicopathological analysis of 34 cases identified in 606 carcinomas. Modern Pathology. 24(8). 1069–1078. 115 indexed citations
19.
Roa, Juan Carlos, Óscar Tapia, Paula Carrasco, et al.. (2006). Prognostic factors of phyllodes tumor of the breast. Pathology International. 56(6). 309–314. 16 indexed citations
20.
Roa, Juan Carlos, Iván Roa, Angélica Melo A, et al.. (2006). Promoter methylation profile in gallbladder cancer. Journal of Gastroenterology. 41(3). 269–275. 31 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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