IDENTIFYING TIME-DELAYED GENE REGULATORY NETWORKS VIA AN EVOLVABLE HIERARCHICAL RECURRENT NEURAL NETWORK

Abstract Background The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design.Interactions in gene regulatory networks (GRNs) include effects of transcription factors, repressors, small metabolites, and microRNA species.In addition, the effects of regulatory inter

Brain-Computer Interfaces (BCIs) translate neuronal information into commands to control external software or hardware, which can improve the quality of life for both healthy and disabled individuals.Here, a multi-modal BCI which combines motor imagery (MI) and steady-state visual evoked potential (SSVEP) is proposed to achieve stable control of a