Iker Badiola

799 citations
39 papers · 641 · h-index 15

Impact in

Papers in

    • Cancer Cells and Metastasis 5
    • Cancer Immunotherapy and Biomarkers 1
    • MicroRNA in disease regulation 4
    • Protease and Inhibitor Mechanisms 1

Iker Badiola

37 papers receiving 625 citations

Peers

Iker Badiola
Comparison fields: 5 of 59
  • Cancer Research 52
  • Food Science 48
  • Oncology 59
  • Hepatology 25
  • Biomaterials 27
Replace Sudeshna Mukherjee with:
Sudeshna Mukherjee India
Alireza Isazadeh Iran
Joana Márquez Spain
Xiaohui Wei China
Yongping Ma China
Tiesuo Zhao China
Nuno Bernardes Portugal
Shaimaa E. Abdel-Ghany Egypt
Hyun-Won Kim South Korea
Iker Badiola relative to Sudeshna Mukherjee India Sudeshna Mukherjee's profile →
Citations per field
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Sudeshna Mukherjee · 1×
Citations per year

Countries citing papers authored by Iker Badiola

Since Specialization
Citations

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

Fields of papers citing papers by Iker Badiola

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Iker Badiola, 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 Iker Badiola Line = papers co-authored together Iker Badiola links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017104
2 200683
3 201163
4 201844
5 202033
6 201831
7 201228
8 201626
9 201520
10 202020
11 201819
12 202219
13 201718
14 202116
15 202216
16 202015
17 202015
18 201811
19 20219
20 20238

About Iker Badiola

Iker Badiola is a scholar working on Oncology, Cancer Research, Hepatology, Infectious Diseases and Sensory Systems, having authored 39 papers that have together received 641 indexed citations. Recurring topics across this work include Cancer Cells and Metastasis (5 papers), Liver physiology and pathology (4 papers), MicroRNA in disease regulation (4 papers), RNA Interference and Gene Delivery (3 papers), Protease and Inhibitor Mechanisms (1 paper), Apelin-related biomedical research (1 paper), Cancer Immunotherapy and Biomarkers (1 paper) and Testicular diseases and treatments (1 paper). The work is most often cited by research in Cancer Research (52 citations), Food Science (48 citations), Oncology (59 citations), Hepatology (25 citations) and Biomaterials (27 citations). Iker Badiola has collaborated with scholars based in Spain, France and Germany. Frequent co-authors include Alejandro Sánchez, Elvira Olaso, Olatz Crende, Abdel‐Majid Khatib, Joana Márquez, Gaskon Ibarretxe, Scott L. Friedman, Fernando Vidal‐Vanaclocha, Fernando J. Unda and Birgit Nørrung. Their work appears in journals such as Cancers, Biology, Cancer Research, BMC Bioinformatics and British Journal of Cancer.

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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