title: On the need for mechanistic models in computational genomics and metagenomics.
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.
authors.affiliation: Department of Molecular Biology, University of Wyoming.
authors.forename: David A
authors.initials: DA
authors.lastname: Liberles
authors.forename: Ashley I
authors.initials: AI
authors.lastname: Teufel
authors.forename: Liang
authors.initials: L
authors.lastname: Liu
authors.forename: Tanja
authors.initials: T
authors.lastname: Stadler
mesh_terms: D001419:Bacteria / Q000235:genetics; D019295:Computational Biology; D004268:DNA-Binding Proteins / Q000235:genetics*; D004463:Ecology; D019143:Evolution, Molecular; D020440:Gene Duplication; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks / Q000235:genetics; D056186:Metagenomics; D008962:Models, Theoretical
chemical_list: D004268:DNA-Binding Proteins
keywords: bacterial ecology; computational biology; gene duplication; molecular evolution; stochastic modeling; transcriptional regulation