Journal of Bioanalysis & Biomedicine

Department of Pediatric Surgery, Shengli Clinical Medical College of Fujian Medical University, Fuzhou 350001, China

Publications

• 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

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