@article{1827, abstract = {Bow-tie or hourglass structure is a common architectural feature found in many biological systems. A bow-tie in a multi-layered structure occurs when intermediate layers have much fewer components than the input and output layers. Examples include metabolism where a handful of building blocks mediate between multiple input nutrients and multiple output biomass components, and signaling networks where information from numerous receptor types passes through a small set of signaling pathways to regulate multiple output genes. Little is known, however, about how bow-tie architectures evolve. Here, we address the evolution of bow-tie architectures using simulations of multi-layered systems evolving to fulfill a given input-output goal. We find that bow-ties spontaneously evolve when the information in the evolutionary goal can be compressed. Mathematically speaking, bow-ties evolve when the rank of the input-output matrix describing the evolutionary goal is deficient. The maximal compression possible (the rank of the goal) determines the size of the narrowest part of the network—that is the bow-tie. A further requirement is that a process is active to reduce the number of links in the network, such as product-rule mutations, otherwise a non-bow-tie solution is found in the evolutionary simulations. This offers a mechanism to understand a common architectural principle of biological systems, and a way to quantitate the effective rank of the goals under which they evolved.}, author = {Friedlander, Tamar and Mayo, Avraham and Tlusty, Tsvi and Alon, Uri}, journal = {PLoS Computational Biology}, number = {3}, publisher = {Public Library of Science}, title = {{Evolution of bow-tie architectures in biology}}, doi = {10.1371/journal.pcbi.1004055}, volume = {11}, year = {2015}, } @article{1809, abstract = {Background: Indirect genetic effects (IGEs) occur when genes expressed in one individual alter the expression of traits in social partners. Previous studies focused on the evolutionary consequences and evolutionary dynamics of IGEs, using equilibrium solutions to predict phenotypes in subsequent generations. However, whether or not such steady states may be reached may depend on the dynamics of interactions themselves. Results: In our study, we focus on the dynamics of social interactions and indirect genetic effects and investigate how they modify phenotypes over time. Unlike previous IGE studies, we do not analyse evolutionary dynamics; rather we consider within-individual phenotypic changes, also referred to as phenotypic plasticity. We analyse iterative interactions, when individuals interact in a series of discontinuous events, and investigate the stability of steady state solutions and the dependence on model parameters, such as population size, strength, and the nature of interactions. We show that for interactions where a feedback loop occurs, the possible parameter space of interaction strength is fairly limited, affecting the evolutionary consequences of IGEs. We discuss the implications of our results for current IGE model predictions and their limitations.}, author = {Trubenova, Barbora and Novak, Sebastian and Hager, Reinmar}, journal = {PLoS One}, number = {5}, publisher = {Public Library of Science}, title = {{Indirect genetic effects and the dynamics of social interactions}}, doi = {10.1371/journal.pone.0126907}, volume = {10}, year = {2015}, } @misc{9772, author = {Trubenova, Barbora and Novak, Sebastian and Hager, Reinmar}, publisher = {Public Library of Science}, title = {{Description of the agent based simulations}}, doi = {10.1371/journal.pone.0126907.s003}, year = {2015}, } @misc{9773, author = {Friedlander, Tamar and Mayo, Avraham E. and Tlusty, Tsvi and Alon, Uri}, publisher = {Public Library of Science}, title = {{Evolutionary simulation code}}, doi = {10.1371/journal.pcbi.1004055.s002}, year = {2015}, } @article{981, abstract = {The tunability of topological surface states and controllable opening of the Dirac gap are of fundamental and practical interest in the field of topological materials. In the newly discovered topological crystalline insulators (TCIs), theory predicts that the Dirac node is protected by a crystalline symmetry and that the surface state electrons can acquire a mass if this symmetry is broken. Recent studies have detected signatures of a spontaneously generated Dirac gap in TCIs; however, the mechanism of mass formation remains elusive. In this work, we present scanning tunnelling microscopy (STM) measurements of the TCI Pb 1â'x Sn x Se for a wide range of alloy compositions spanning the topological and non-topological regimes. The STM topographies reveal a symmetry-breaking distortion on the surface, which imparts mass to the otherwise massless Dirac electrons-a mechanism analogous to the long sought-after Higgs mechanism in particle physics. Interestingly, the measured Dirac gap decreases on approaching the trivial phase, whereas the magnitude of the distortion remains nearly constant. Our data and calculations reveal that the penetration depth of Dirac surface states controls the magnitude of the Dirac mass. At the limit of the critical composition, the penetration depth is predicted to go to infinity, resulting in zero mass, consistent with our measurements. Finally, we discover the existence of surface states in the non-topological regime, which have the characteristics of gapped, double-branched Dirac fermions and could be exploited in realizing superconductivity in these materials.}, author = {Zeljkovic, Ilija and Okada, Yoshinori and Maksym Serbyn and Sankar, Raman and Walkup, Daniel and Zhou, Wenwen and Liu, Junwei and Chang, Guoqing and Wang, Yungjui and Hasan, Md Z and Chou, Fangcheng and Lin, Hsin and Bansil, Arun and Fu, Liang and Madhavan, Vidya}, journal = {Nature Materials}, number = {3}, pages = {318 -- 324}, publisher = {Nature Publishing Group}, title = {{Dirac mass generation from crystal symmetry breaking on the surfaces of topological crystalline insulators}}, doi = {10.1038/nmat4215}, volume = {14}, year = {2015}, }