About this Research Topic
The ultimate objective is therefore to investigate the factors directly involved in the development of breast cancer drug resistance and to overcome this problem. Alternatively, novel drug targets (biomarkers) may help to overcome the problem of drug resistance in breast cancer. In silico studies. particularly using artificial intelligence and machine learning methods, can be implemented to predict the structural implications of mutations. This will be beneficial in understanding mechanisms of drug resistance and the discovery of novel biomarkers and drugs.
In this Research Topic we aim to provide an overview of recent technologies, such as artificial intelligence or machine learning approaches, relevant to breast cancer diagnosis, management, treatment, and the development of different biomarkers. Original Research articles, mini-reviews and full length review articles covering breast cancer are welcome. We encourage submissions covering, but not limited to, the following topics:
• Artificial intelligence or machine learning approaches in breast cancer diagnosis
• Discovery of novel biomarkers in breast cancer
• Machine learning based drug discovery
• Molecular dynamics simulation to understand different mechanisms in breast cancer
• Structural implications of drug resistance in Breast cancer
• Breast cancer resistance prediction
Keywords: Breast Cancer, Artificial Intelligence, Mutation, Resistance, Biomarkers discovery
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.