Recent Posts
- Principles of biological computation: from circadian clock to evolution
- The science and engineering of biological computation: from process to software to DNA-based neural networks
- Elements of biological computation & stochastic thermodynamics of life
- Rationality, the Bayesian mind and their limits
- Web of C-lief: conjectures vs. model assumptions vs. scientific beliefs
- Idealization vs abstraction for mathematical models of evolution
- Allegory of the replication crisis in algorithmic trading
- 668,215 views
Join 2,752 other subscribers
Contributing authors
-
Abel Molina
-
Alexandru Strimbu
-
Alexander Yartsev
-
Eric Bolo
-
David Robert Grimes
-
Forrest Barnum
-
Jill Gallaher
-
Julian Xue
-
Artem Kaznatcheev
-
Keven Poulin
-
Marcel Montrey
-
Matthew Wicker
-
Dan Nichol
-
Philip Gerlee
-
Piotr MigdaĆ
-
Robert Vander Velde
-
Rob Noble
-
Sergio Graziosi
-
Max Hartshorn
-
Thomas Shultz
-
Vincent Cannataro
-
Yunjun Yang
Description before prediction: evolutionary games in oncology
June 29, 2019 by Artem Kaznatcheev Leave a comment
As I discussed towards the end of an old post on cross-validation and prediction: we don’t always want to have prediction as our primary goal, or metric of success. In fact, I think that if a discipline has not found a vocabulary for its basic terms, a grammar for combining those terms, and a framework for collecting, interpreting, and/or translating experimental practice into those terms then focusing on prediction can actually slow us down or push us in the wrong direction. To adapt Knuth: I suspect that premature optimization of predictive potential is the root of all evil.
We need to first have a good framework for describing and summarizing phenomena before we set out to build theories within that framework for predicting phenomena.
In this brief post, I want to ask if evolutionary games in oncology are ready for building predictive models. Or if they are still in need of establishing themselves as a good descriptive framework.
Read more of this post
Filed under Commentary, Preliminary Tagged with mathematical oncology, operationalization, philosophy of science, replicator dynamics