title: A systems approach to integrative biology: an overview of statistical methods to elucidate association and architecture.
abstract: An organism's ability to maintain a desired physiological response relies extensively on how cellular and molecular signaling networks interpret and react to environmental cues. The capacity to quantitatively predict how networks respond to a changing environment by modifying signaling regulation and phenotypic responses will help inform and predict the impact of a changing global enivronment on organisms and ecosystems. Many computational strategies have been developed to resolve cue-signal-response networks. However, selecting a strategy that answers a specific biological question requires knowledge both of the type of data being collected, and of the strengths and weaknesses of different computational regimes. We broadly explore several computational approaches, and we evaluate their accuracy in predicting a given response. Specifically, we describe how statistical algorithms can be used in the context of integrative and comparative biology to elucidate the genomic, proteomic, and/or cellular networks responsible for robust physiological response. As a case study, we apply this strategy to a dataset of quantitative levels of protein abundance from the mussel, Mytilus galloprovincialis, to uncover the temperature-dependent signaling network.
authors.affiliation: *Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA; Interdepartmental Biological Sciences, Northwestern University, Evanston, IL, USA.
authors.forename: Mark F
authors.initials: MF
authors.lastname: Ciaccio
authors.affiliation: *Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA; Interdepartmental Biological Sciences, Northwestern University, Evanston, IL, USA.
authors.forename: Justin D
authors.initials: JD
authors.lastname: Finkle
authors.affiliation: *Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA; Interdepartmental Biological Sciences, Northwestern University, Evanston, IL, USA.
authors.forename: Albert Y
authors.initials: AY
authors.lastname: Xue
authors.affiliation: *Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA; Interdepartmental Biological Sciences, Northwestern University, Evanston, IL, USA*Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA; Interdepartmental Biological Sciences, Northwestern University, Evanston, IL, USA n-bagheri@northwestern.edu.
authors.forename: Neda
authors.initials: N
authors.lastname: Bagheri
mesh_terms: D000818:Animals; D023281:Genomics; D008954:Models, Biological; D049878:Mytilus / Q000502:physiology*; D040901:Proteomics; D015398:Signal Transduction; D049490:Systems Biology / Q000379:methods*; D013696:Temperature