A machine learning approach to identify predictive molecular markers for cisplatin chemosensitivity following surgical resection in ovarian cancer

Ovarian cancer is associated with poor prognosis. Platinum resistance contributes significantly to the high rate of tumour recurrence. We aimed to identify a set of molecular markers for predicting platinum sensitivity. A signature predicting cisplatin sensitivity was generated using the Genomics of...

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Detalles Bibliográficos
Autores principales: Shannon, Nicholas Brian, Tan, Laura Ling Ying, Tan, Qiu Xuan, Tan, Joey Wee-Shan, Hendrikson, Josephine, Ng, Wai Har, Ng, Gillian, Liu, Ying, Ong, Xing-Yi Sarah, Nadarajah, Ravichandran, Wong, Jolene Si Min, Tan, Grace Hwei Ching, Soo, Khee Chee, Teo, Melissa Ching Ching, Chia, Claramae Shulyn, Ong, Chin-Ann Johnny
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377048/
https://www.ncbi.nlm.nih.gov/pubmed/34413360
http://dx.doi.org/10.1038/s41598-021-96072-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377048/
https://www.ncbi.nlm.nih.gov/pubmed/34413360
http://dx.doi.org/10.1038/s41598-021-96072-6

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