Cancer, a class of diseases characterized by out-of-control cell growth, is the second most common cause of death and greatly threatens people’s health. According to the survey of the World Health Organization in 2012, there were four million new cancer cases and 8.2 million cancer-related deaths worldwide. Over the last few years, there have been huge amounts of data about diagnosis and treatment of cancer, which is generated from the developments of the biomedical technologies and approaches. The opportunities from the big data in healthcare open a new window to improve clinical diagnoses or therapeutics, but there are many challenges in efficient analysis and interpretation of such big and complex data. For instance, how to manage, extract, analyze, integrate, visualize, and communicate the hidden information from the myriad of data representation of cancer evolved into one of the greatest challenges in next-generation biomedicine. Thus, there is a need to fundamentally address all the above-mentioned issues in big data in cancer healthcare.

BioMed Research International seeks original manuscripts for a Special Issue on the theme: Analysis and Modeling for Big Data in Cancer Research, scheduled to appear in an issue of 2017.

Potential topics include but are not limited to the following:

• Big data analytics for genomics, transcriptomics, and metabolomics in cancer research
• New computational methods such as machine learning, scalability/parallelization, map-reduce paradigm, and network analytics, used for big data analysis within cancer
• Analysis of the next-generation sequencing (NGS) and big data (including gene expression profile) for cancer research
• Analysis of the spectroscopy/mass spectrometry mass of macromolecule
• Big data in Chinese medicine
• Standardized data collection to build prediction models in oncology
• Big data for cancer signaling pathway study
• Application of big data for cancer biomarker discovery and validation
• Big data for cancer drug discovery