Department of Pediatric Surgery, Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350001, China
Mini Review
Harnessing Multi-omics and Machine Learning for Predictive Modeling of Cancer Drug Response: Advancing Precision Medicine
Author(s): Richard Fernandes*
The advent of precision medicine has revolutionized oncology by promising tailored therapeutic strategies based on individual patient
characteristics. Central to this advancement is the integration of multi-omics data—genomics, transcriptomics, proteomics, and metabolomics—
providing a comprehensive understanding of cancer's molecular underpinnings. This study explores the integration of machine learning algorithms
for predictive modeling of drug response in cancer patients using a multi-omics approach. By leveraging advanced computational techniques and
vast multi-omics datasets, the research aims to enhance the accuracy and efficacy of predicting patient-specific responses to cancer treatments,
thereby facilitating personalized medicine. Key challenges such as cancer heterogeneity, high dimensionality of data, and integration of disparate
data typ.. Read More»
DOI:
10.37421/1948-593X.2024.16.432
Journal of Bioanalysis & Biomedicine received 3099 citations as per Google Scholar report
Spanish 
Chinese 
Russian 
German 
French 
Japanese 
Portuguese 
Hindi 