Pablo Pinto

486 citations
15 papers · 304 · h-index 9

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
    • Circular RNAs in diseases
    • RNA modifications and cancer
    • Cell death mechanisms and regulation

Papers in

Pablo Pinto

15 papers receiving 300 citations

Peers

Pablo Pinto
Comparison fields: 5 of 75
  • Cancer Research 88
  • Molecular Biology 179
  • Pathology and Forensic Medicine 38
  • Pharmacology 14
  • Infectious Diseases 24
Replace Xinye Wang with:
Xinye Wang China
Neeraj Kumar India
Shasha Hou China
João Crispim Encarnação Portugal
Keun Young Kim South Korea
Ting Xiong China
Tong Xie China
Xiaoshuo Dai China
Pablo Pinto relative to Xinye Wang China Xinye Wang's profile →
Citations per field
00.5×1.5×1.9×
Xinye Wang · 1×
Citations per year

Countries citing papers authored by Pablo Pinto

Since Specialization
Citations

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

Fields of papers citing papers by Pablo Pinto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Pablo Pinto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Pablo Pinto Line = papers co-authored together Pablo Pinto links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2019165
2 201729
3 202021
4 201918
5 202017
6 201612
7 202011
8 20139
9 20208
10 20127
11 20213
12 20241
13 20221
14 20241
15 20231

About Pablo Pinto

Pablo Pinto is a scholar working on Molecular Biology, Epidemiology, Cancer Research, Infectious Diseases and Immunology, having authored 15 papers that have together received 304 indexed citations. Recurring topics across this work include MicroRNA in disease regulation (5 papers), Mycobacterium research and diagnosis (4 papers), Tuberculosis Research and Epidemiology (3 papers), Cancer-related molecular mechanisms research (3 papers), Leprosy Research and Treatment (2 papers), Forensic and Genetic Research (1 paper), Machine Learning in Bioinformatics (1 paper) and Genetic factors in colorectal cancer (1 paper). The work is most often cited by research in Cancer Research (88 citations), Molecular Biology (179 citations), Pathology and Forensic Medicine (38 citations), Pharmacology (14 citations) and Infectious Diseases (24 citations). Pablo Pinto has collaborated with scholars based in Brazil and United States. Frequent co-authors include Ândrea Ribeiro‐dos‐Santos, Amanda Ferreira Vidal, Giovanna C. Cavalcante, Sidney Emanuel Batista dos Santos, Paulo Pimentel de Assumpção, Leandro Magalhães, Sâmia Demachki, Ney Pereira Carneiro dos Santos, Mara Helena Hutz and Cláudio Guedes Salgado. Their work appears in journals such as Scientific Reports, Frontiers in Genetics, International Journal of Molecular Sciences, PLoS ONE and International Journal of Infectious Diseases.

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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