Hello,
I'm looking to inquire about what Python packages everyone uses for Deep Learning, Neural Networks, AI, ML, and all of that good stuff for things in regard to whole genome sequencing annotation or even just your own use case. Trying to spark some ideas for my current task at hand. Thank you.
If you could also provide why you choose to use your recommendation/suggestion it would be very helpful.
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screadore •
I guess the big python packages would be scikit-learn, pytorch, and TensorFlow, but I can't say that they see a lot of use in day-to-day bioinformatics analyses. Neural networks are relatively common for various types of analyses. HMMs are sort of used for genome annotations though, particularly for things like chromatin state.
If you elaborate on your task, folks may have more thorough recommendations for both packages and approach.
Well I want to implement AI or ML to map our conditions reported from our samples to HPO terms so use in an automation script for running variant annotations.
It's already fairly easy to map the HPO terms to genes using their API or manually after downloading their annotations. You may be able to do what you want with simpler methods.
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