Arno Steinacher
University of Exeter
10 Papers
18 Citations
Arno Steinacher is an academic researcher from University of Exeter. The author has contributed to research in topics: Monophyly & Phylogenetic tree. The author has an hindex of 8, co-authored 10 publications. Previous affiliations of Arno Steinacher include University of Cambridge & University of Sheffield.
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Papers
Testing for misleading effects in the phylogenetic reconstruction of ancient lineages of hexapods: influence of character dependence and character choice in analyses of 28S rRNA sequences
Emiliano Dell'Ampio,Nikolaus U. Szucsich,Antonio Carapelli,Francesco Frati,Gerhard Steiner,Arno Steinacher,Günther Pass +6 more
TL;DR: The phylogenetic signal of the complete sequences of the 28S rRNA gene favours monophyly of Hexapoda over paraphyly, however, further corroboration from independent data is needed to rule out the competing hypothesis of mutually paraphyletic Crustacea and Hexapod.
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Evolutionary Principles Underlying Structure and Response Dynamics of Cellular Networks
Arno Steinacher,Orkun S. Soyer +1 more
TL;DR: It is argued that this evolutionary framework could lead to deciphering evolutionary origin and relevance of proposed design principles, thereby allowing to predict their presence or absence in an organism based on its environment and biochemistry and their effect on its future evolution.
16
On the role of ultrasensitivity in biomolecular control systems
Francesco Montefusco,Arno Steinacher,Ozgur E. Akman,Declan G. Bates,Orkun S. Soyer +4 more
- 01 Dec 2012
TL;DR: It is found that a proportional controller implementing ultrasensitivity allows more precise and faster adaptation of cell volume following an osmo-shock, and should be of interest to synthetic biologists attempting to design biomolecular control systems.
2
Computer simulation: The imaginary friend of auxin transport biology
TL;DR: This work focuses on self‐organising models for polar auxin transport and on recent attempts to unify conflicting mechanistic explanations, and in general how computer simulations are proving to be increasingly effective in hypothesis generation and testing, and how simulation can be used to direct future experiments.
Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.
TL;DR: A possible solution to the robustness-evolvability trade-off is provided, an explanation for the ubiquity of nonlinear dynamics in gene expression networks is suggested, and useful guidelines for the design of synthetic gene circuits are generated.