Tag: Computational Biology

Genetic studies have provided us with countless examples of regulatory switches that transduce a signal into a response. Mutant analysis is usually sufficient to identify these controlling elements, but often in an all-or-nothing way. Here, Ghusinga et al. have taken a theoretical kinetic approach to…

Crassulacean acid metabolism (CAM) is a photosynthetic adaptation pathway in arid environments to minimize water loss by opening the stomata at night, when the temperature and therefore water loss due to transpiration is lower. Carbon dioxide is initially fixed at night and stored in the vacuole. Engineering…

Many proteins polarize in the cell creating a subcellular niche for various functions. Asymmetric distribution of proteins is a general mechanism for localized growth, directional long-range signaling, cell migration, and asymmetric cell divisions. Well-known examples of polarity proteins include PIN-FORMED1…

Leucine-rich repeat receptor-like kinases (LRR-RLKs) act as signaling receptors, are the largest plant-specific protein kinase family, and are involved in myriad developmental activities and defense systems. Due to the large number of proteins in this group, their diversification and consequent redundancy…

As sessile organisms, plants must not only respond to a single stress, but multiple stresses at the same time. To understand the DNA regulatory elements that mediate the transcriptional response to heat, drought and combined heat and drought stress, Azodi et al. utilized the known transcription factor…

Throughout the plant science community, the use of computational or in silico analyses which precede traditional studies are gaining traction to identify research opportunities. Multiscale computational models are those which assimilate data from all biological system levels from gene to ecosystem. Benes…

One of the goals of plant science is to use the molecular phenotype (genome, transcriptome, proteome) to predict the whole-plant phenotype. Deep learning approaches can potentially begin to do this, starting with a training dataset, and testing it with a validation dataset. Wang et al. review advances…

If you want a great plant, select for a strong, vigorous, high-yielding individual; this is also the outcome of natural selection. But if you want a great field of plants, these traits may not be as suitable, because the plants will expend energy competing between themselves. When seeds from many plants…