title: Can all heritable biology really be reduced to a single dimension?
abstract: A long-held presupposition in the field of bioinformatics holds that genetic, and now even epigenetic 'information' can be abstracted from the physicochemical details of the macromolecular polymers in which it resides. It is perhaps rather ironic that this basic conjecture originated upon the first observations of DNA structure itself. This static model of DNA led very quickly to the conclusion that only the nucleobase sequence itself is rich enough in molecular complexity to replicate a complex biology. This idea has been pervasive throughout genomic science, higher education and popular culture ever since; to the point that most of us would accept it unquestioningly as fact. What is more alarming is that this conjecture is driving a significant portion of the technological development in modern genomics towards methods strongly rooted in DNA sequencing, thereby reducing a dynamic multi-dimensional biology into single-dimensional forms of data. Evidence countering this central tenet of bioinformatics has been quietly mounting over many decades, prompting some to propose that the genome must be studied from the perspective of its molecular reality, rather than as a body of information to be represented symbolically. Here, we explore the epistemological boundary between bioinformatics and molecular biology, and warn against an 'overtly' bioinformatic perspective. We review a selection of new bioinformatic methods that move beyond sequence-based approaches to include consideration of databased three dimensional structures. However, we also note that these hybrid methods still ignore the most important element of gene function when attempting to improve outcomes; the fourth dimension of molecular dynamics over time.
authors.affiliation: Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester 14623, NY, USA. Electronic address: gabsbi@rit.edu.
authors.forename: Gregory A
authors.initials: GA
authors.lastname: Babbitt
authors.affiliation: Biomedical Engineering, Rochester Institute of Technology, Rochester 14623, NY, USA.
authors.forename: Erin E
authors.initials: EE
authors.lastname: Coppola
authors.affiliation: B. Golisano College of Computing and Information Sciences, Rochester Institute of Technology, Rochester 14623, NY, USA.
authors.forename: Mohammed A
authors.initials: MA
authors.lastname: Alawad
authors.affiliation: Thomas H. Gosnell School of Life Sciences, Rochester Institute of Technology, Rochester 14623, NY, USA.
authors.forename: André O
authors.initials: AO
authors.lastname: Hudson
mesh_terms: D019295:Computational Biology / Q000639:trends*; D004247:DNA / Q000737:chemistry / Q000235:genetics*; D023281:Genomics; D056004:Molecular Dynamics Simulation / Q000639:trends*; D009154:Mutation; D009690:Nucleic Acid Conformation; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry / Q000235:genetics*; D017422:Sequence Analysis, DNA
chemical_list: D011506:Proteins; D004247:DNA
keywords: Bioinformatics; DNA sequencing; Epigenetics; Gene; Genetics; Molecular biology; Molecular dynamics; Mutation; Nucleic acids; Protein structure