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The article focuses on a workshop held at the European Molecular Biology Laboratory called "Predicting evolution" which explored the predictability of evolutionary biology with the help of computational and theoretical approaches and the integration of empirical evolutionary information. It mentions that the discussions held at the workshop on evolution of biological systems at various levels from genes and molecules to organism development and ecology.

Predicting evolutionary outcomes is an important research goal in a diversity of contexts. The focus of evolutionary forecasting is usually on adaptive processes, and efforts to improve prediction typically focus on selection. However, adaptive processes often rely on new mutations, which can be strongly influenced by predictable biases in mutation. Here, we provide an overview of existing theory and evidence for such mutation-biased adaptation and consider the implications of these results for the problem of prediction, in regard to topics such as the evolution of infectious diseases, resistance to biochemical agents, as well as cancer and other kinds of somatic evolution. We argue that empirical knowledge of mutational biases is likely to improve in the near future, and that this knowledge is readily applicable to the challenges of short-term prediction. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'. [ABSTRACT FROM AUTHOR]