Gene

Functional genomics

Biology

Computer science

Computational genomics

Genetics

Genome

RNA splicing

Genomics

Data science

Artificial intelligence

Deep learning

Machine learning

Nature Reviews Genetics

As a data-driven science, genomics largely utilizes machine learning to capture dependencies in data and derive novel biological hypotheses. However, the ability to extract new insights from the exponentially increasing volume of genomics data requires more expressive machine learning models. By effectively leveraging large data sets, deep learning has transformed fields such as computer vision and natural language processing. Now, it is becoming the method of choice for many genomics modelling tasks, including predicting the impact of genetic variation on gene regulatory mechanisms such as DNA accessibility and splicing. This Review describes different deep learning techniques and how they can be applied to extract biologically relevant information from large, complex genomic data sets.

Deep learning: new computational modelling techniques for genomics