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The transcription process of DNA is highly complex and while short DNA sequence motifs recognized by transcription factors are well known, less is known about the context in the DNA sequence that determines whether a transcription factor will actually bind its motif. Zheng and colleagues present a method that uses convolutional neural networks to identify sequence features that help predict whether transcribing proteins can bind to their target sequences in DNA.
Microrobotics offers great potential for precise drug delivery as medication can be released in the bloodstream only where it is needed. But the dynamic environment of the bloodstream is a challenge for navigation. An approach presented by Ahmed and colleagues combines magnetic and acoustic fields to allow swarms of particles to swim against a current.
The annotation of the visual signs of emotions can be important for psychological studies and even human–computer interactions. Instead of only ascribing discrete emotions, Toisoul and colleagues use a single neural network that predicts emotional labels on a spectrum of valence and arousal without separate face-alignment steps.
Reticular frameworks are crystalline porous materials with desirable properties such as gas separation, but their large design space presents a challenge. An automated nanoporous materials discovery platform powered by a supramolecular variational autoencoder can efficiently explore this space.
Turbulence modelling is an essential flow simulation tool, but is typically dependent on physical insight and engineering intuition. Novati et al. develop a multi-agent reinforcement learning approach for learning turbulence models that can generalize across grid sizes and flow conditions.
Many approved drugs can be used to treat diseases other than the one they were developed for, which has the added benefit that the safety of the drug has already been tested. To identify possible candidates for re-purposing trials, Liu et al. have developed a method to use existing electronic patient data to simulate clinical trials and identify drugs that influence the progression of diseases with which they were not previously associated.
