Abstract
Computational genomics is now generating very large volumes of data that have the potential to be used to address important questions in both basic biology and biomedicine. Addressing these important biological questions becomes possible when mechanistic models rooted in biochemistry and evolutionary/population genetic processes are developed, instead of fitting data to off-the-shelf statistical distributions that do not enable mechanistic inference. Three examples are presented, the first involving ecological processes inferred from metagenomic data, the second involving mechanisms of gene regulation rooted in protein-DNA interactions with consideration of DNA structure, and the third involving existing models for the retention of duplicate genes that enables prediction of evolutionary mechanisms. This description of mechanistic models is generalized toward future developments in computational genomics and the need for biological mechanisms and processes in biological models.