Welcome — why combiola?

Uniting the twin stars of computational biology and machine learning bring results that are out of this world :)

Biology is enormously complex. We have a huge amount to learn about the systems and networks governing our bodies, and how and why they change during health and disease states.

Computational biology is making huge strides in bringing colossal compute resources to bear on the genome and epigenome, constituting some of the most complex analytical questions humanity has faced, however there is so much more to do.

Machine learning meanwhile has made advances in many fields, achieving near human-level performance in a range of tasks, and even super-human performance in some! Image-recognition, object detection and speech recognition and generation are just some of these areas where innovation have flourished and results exceeded reasonable expectations.

The effective fusion of computational biology and machine learning is occurring more frequently but is still in its infancy.

There is a small but growing band of convergent practitioners around the world with deep expertise in both fields.

Combiola (computational biology + learning algorithms) is a place for these researchers to come together, teach and recap on best-practices, share ideas — and by all means discuss outlandish creative ideas that are still a long way from being ready for publication prime-time.

Combiola

where comp bio & learning algorithms meet

Charlie Campbell Roberts

Written by

Medically-trained entrepreneur & investor; co-founder of Freenome, a startup backed by leading VCs to deploy ML on cell-free DNA from blood for cancer detection

Combiola

Combiola

where comp bio & learning algorithms meet

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