Best practices for applying deep learning to genomics

So far, we have seen several challenges with DL for genomics and common pitfalls and how to avoid them. To make the best use of DL for genomics, let’s look at a collection of some best practices to follow while leveraging DL for genomics.

Understand the problem and know your data better

As seen in the DL life cycle, the most important aspect of DL is understanding the business goal or scientific question that you are trying to solve and then framing the business goal into a DL problem. Having a proper understanding of the scientific question (business goal) and a clear analysis plan (framing the business goal into a DL problem) are key to the success of DL projects in genomics. You should not even start working on DL without defining the goals of the project. For instance, would you step into the lab without thinking about what you plan to do that day? No. Right? Some of the key questions that you should be asking to...