Special Issue on Bioinformatics and Artificial Intelligence for Biomarker Discovery

Recently, myriad multi-omics data from clinical and biomedical studies have been accumulated for biomarker discovery. It is challenging for scientists to deal with these big datasets and there is an urgent need to develop relevant bioinformatics and artificial intelligence methods for efficient biomarker discovery through analysis, integration and interpretation of heterogeneous multi-omics data. In this special issue, we seek papers that consider these methods, including the mining of genomes, epigenome, transcriptomes, metagenomes, metabolomes and proteomes in relation to health and diseases. Research and methodological studies will be considered. High-quality narrative, commentary and systematic reviews will be also considered.

Topics Covered:

These will include, but not be limited to:

• An artificial intelligence (AI) approach for biomarker discovery
• Machine learning (ML) methods for extracting biomarkers from multi-omics data and other datasets (e.g., CRISPR screening)
• Multi-omics data integration and mining for biomarker discovery
• Statistical and mathematical modelling for biomarker discovery
• Dynamic biomarker discovery from time series analysis
• Visualisation techniques and software for biomarker discovery
• Complex network methods for biomarker discovery

Important Dates & Deadlines:

• Submission of papers: rolling submission

Guest Editors:

• Prof. Xingpeng Jiang, Central China Normal University, China. Email: xpjiang@mail.ccnu.edu.cn
• Prof. Xuefeng Cui, School of Computer Science and Technology, Shandong University, China. Email: xfcui.uw@gmail.com