An Integrative Data Mining and Omics-Based Translational Model for the Identification and Validation of Oncogenic Biomarkers of Pancreatic Cancer

An Integrative Data Mining and Omics-Based Translational Model for the Identification and Validation of Oncogenic Biomarkers of Pancreatic Cancer

Substantial alterations at the multi-omics level of pancreatic cancer (PC) impede the possibility to diagnose and treat patients in early stages. Herein, we conducted an integrative omics-based translational analysis, utilizing next-generation sequencing, transcriptome meta-analysis, and immunohisto...

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Bibliographic Details
Main Authors: Nguyen Phuoc Long, Kyung Hee Jung, Nguyen Hoang Anh, Hong Hua Yan, Tran Diem Nghi, Seongoh Park, Sang Jun Yoon, Jung Eun Min, Hyung Min Kim, Joo Han Lim, Joon Mee Kim, Johan Lim, Sanghyuk Lee, Soon-Sun Hong, Sung Won Kwon
Format: Article
Language:English
Published: MDPI AG 2019-01-01
Series:Cancers
Subjects:
pancreatic ductal adenocarcinoma
systems biology
meta-analysis
machine learning
next-generation sequencing
transcriptomics
diagnostic biomarker
prognostic biomarker
Online Access:https://www.mdpi.com/2072-6694/11/2/155

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https://www.mdpi.com/2072-6694/11/2/155

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