Hi everyone,

I have been working mostly with RNA-seq and single cell data and transcript-level analyses, but I have not yet built a machine learning focused project. I would really like to get started in that direction, ideally in the context of human disease, especially cancer, though I am open to other areas as well.

I am looking for realistic project ideas that a graduate student could execute using public datasets (e.g., TCGA, GEO). Something that’s biologically meaningful but not overwhelmingly complex.

Also, are there any well-structured GitHub repositories or example projects that would be good to follow along with and then adapt into my own project?

I would appreciate any suggestions or advice on how to approach this transition into ML within bioinformatics.