Current Progress of Bioinformatics for Human Health

Massive biological data provides a broad view to understand the dynamics of human health status and disease from multiple aspects. During the past decade, the tremendous volume of biological data has been produced in different ways. How to analyze the high-volume data precisely and efficiently, and take advantage from it has become one of the most essential bottlenecks for precision medicine. Newly developed bioinformatics tools are bringing opportunities for these challenges, from sequence-based algorithms such as genome assembly and genome comparison, to disease classifiers like regular machine learning and neural network. In this chapter, we summarize the widely-used state-of-the-art computational approaches of multi-omics data to study human health and diseases, including bioinformatics methods and tools for genomics, transcriptomics, metagenomics, and single-cell data, as well as machine learning algorithms and strategies.