Peer-reviewedCC BY 4.0Frontiers in Oncology28 Oct 2026

Editorial: Decoding cancer complexity with artificial intelligence and molecular level studies: informatics-driven approaches for therapeutic innovation

Chandrabose Selvaraj¹
Krishnendu Bera²
Senthilkumar Krishnamoorthi³
Sajitha Lulu S⁴

4 affiliations

¹CSRDD Lab, Bioinformatics Division, Department of Marine Biotechnology, AMET University (Deemed to Be University)
²Living Systems Institute, Stocker Road, University of Exeter
³Foundation Traditional Chinese Medicine Research Institute for Age-related Diseases (MFRI), School of Chinese Medicine, Hong Kong Baptist University
⁴Integrative Multiomics Lab, School of Bio Sciences and Technology, Vellore Institute of Technology

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BibTeX

@article{selvaraj2026editorial,
  title = {{Editorial: Decoding cancer complexity with artificial intelligence and molecular level studies: informatics-driven approaches for therapeutic innovation}},
  author = {Chandrabose Selvaraj and Krishnendu Bera and Senthilkumar Krishnamoorthi and Sajitha Lulu S},
  journal = {Frontiers in Oncology},
  year = {2026},
  month = oct,
  doi = {10.3389/fonc.2026.2008527},
  url = {https://www.frontiersin.org/articles/10.3389/fonc.2026.2008527/full},
  note = {CC BY 4.0},
}

RIS

TY  - JOUR
TI  - Editorial: Decoding cancer complexity with artificial intelligence and molecular level studies: informatics-driven approaches for therapeutic innovation
AU  - Chandrabose Selvaraj
AU  - Krishnendu Bera
AU  - Senthilkumar Krishnamoorthi
AU  - Sajitha Lulu S
PY  - 2026
DA  - 2026/10/28
JO  - Frontiers in Oncology
DO  - 10.3389/fonc.2026.2008527
UR  - https://www.frontiersin.org/articles/10.3389/fonc.2026.2008527/full
SN  - 2234-943X
ER  -

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