What's Next?

Congratulations

You have completed the Genomics course. You now understand the molecular biology behind AlphaGenome — DNA sequences, gene expression, splicing, regulatory elements, and variant effect prediction.

What to Explore Next

  • Run AlphaGenome yourself -- The model is available for non-commercial use via the Python SDK at deepmind.google.com/science/alphagenome.
  • Enformer -- DeepMind's earlier genomics model (2021), which AlphaGenome improves upon. The original paper is a good read.
  • Bioinformatics with Biopython -- The biopython library implements professional versions of everything in this course.
  • ENCODE Project -- The experimental dataset that underpins AlphaGenome's training data.
  • GTEx -- Gene expression across human tissues; another key AlphaGenome training resource.

Tools and Libraries

  • Biopython -- The standard Python library for bioinformatics.
  • pysam -- Reading genome alignment files.
  • pyBigWig -- Reading genomic signal tracks.
  • Kipooi -- A model zoo for genomics ML models.

Further Reading

  • Molecular Biology of the Gene by Watson et al. -- The canonical textbook.
  • Bioinformatics Algorithms by Compeau & Pevzner -- Algorithmic approach to genomics.
  • AlphaGenome paper on Nature -- The original publication.
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