Deep learning has become increasingly important for analysis of omics data. The techinque has become particularly important for studying structures by generating synthetic samples.The results obtained are not as simple as those obtained with image application. Deep learning has given excellent results with image data.
Hess M. et. al. (2020) have shown the application of log- linear models in extracting patterns from omics data. They have illustrated the technique on simulated as well as cortical single- cell gene expression data.The technique can be used to gain biological insights from omics data. The code is available on github at the following URL: https://github.com/ssehztirom/Exploring-generative-deep-learning-for-omics-data-by-using-log-linear-models.
Reference:
Hess M. et. al. (2020) Exploring generative deep learning for omics data using log-linear models. Bioinformatics 36(20):5045-5053