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02/22/2018

research article

Memory functions reveal structural properties of gene regulatory networks

Gene regulatory networks are essential for cell fate specification. But the recursive links that comprise these networks often make determining their properties and behaviour complicated. Computational models of these networks can also be difficult to decipher. To reduce the complexity of such models, Herrera-Delgado et al. employ a Zwanzig-Mori projection approach.

Image credit: Herrera-Delgado et al.

Memory functions reveal structural properties of gene regulatory networks

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Current Issue January 2018

02/16/2018

research article

Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield

Can cells achieve high growth rates and yields simultaneously, or is there a conflict between theses two goals? Using a new method called Enzymatic Flux Cost Minimization (EFCM), Wortel et al. predict cellular growth rates and find that growth rate/yield trade-offs and the ensuing preference for enzyme-efficient or substrate-efficient metabolic pathways are not universal, but depend on growth conditions such as external glucose.

Image credit: Wortel et al.

Metabolic enzyme cost explains variable trade-offs between microbial growth rate and yield

02/20/2018

research article

Exploiting the geometry of the solution space to reduce sensitivity to neuromotor noise

Throwing is a skill that requires a high degree of coordination to successfully hit a target. In this study, Zhang et al. demonstrate that humans can overcome seemingly stringent timing requirements when throwing by shaping their hand trajectories to create extended timing windows, where ball releases achieve target hits despite temporal imprecision.

Image credit: KeithJJ/ pixabay.com

Exploiting the geometry of the solution space to reduce sensitivity to neuromotor noise

02/16/2018

research article

A stochastic and dynamical view of pluripotency in mouse embryonic stem cells

Thanks to advances in high-throughput sequencing and related computational tools for data analysis, we are beginning to unravel basic topological features of pluripotency networks. Here Lin et al. propose a computational framework that offers a way of bridging the divide between Boolean networks and higher resolution views of networks in a predictive and quantitative manner. 

A stochastic and dynamical view of pluripotency in mouse embryonic stem cells

Image credit: Alexas_Fotos/ pixabay.com

02/23/2018

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